For any intuitionistic multi-fuzzy set A = { < x , µA(x) , νA(x) > : x∈X} of an universe set X, we study the set [A](α, β) called the (α, β)–lower cut of A. It is the crisp multi-set { x∈X : µi(x) ≤ αi , νi(x) ≥ βi , ∀i } of X. In this paper, an attempt has been made to study some algebraic structure of intuitionistic multi-anti fuzzy subgroups and their properties with the help of their (α, β)–lower cut sets
Y.B.Jun et al. [9] introduced the notion of Cubic sets and Cubic subgroups. In this paper we introduced the
notion of cubic BF- Algebra i.e., an interval-valued BF-Algebra and an anti fuzzy BF-Algebra. Intersection of two cubic
BF- Algebras is again a cubic BF-Algebra is also studied.
Pseudo Bipolar Fuzzy Cosets of Bipolar Fuzzy and Bipolar Anti-Fuzzy HX Subgroupsmathsjournal
In this paper, we introduce the concept of pseudo bipolar fuzzy cosets, pseudo bipolar fuzzy double cosets of a bipolar fuzzy and bipolar anti-fuzzy subgroups. We also establish these concepts to bipolar fuzzy and bipolar anti-fuzzy HX subgroups of a HX group with suitable examples. Also we discuss some of their relative properties.
In this paper we introduce the notions of Fuzzy Ideals in BH-algebras and the notion
of fuzzy dot Ideals of BH-algebras and investigate some of their results.
Intuitionistic Fuzzification of T-Ideals in Bci-Algebrasiosrjce
The notions of intuitionistic fuzzy T-ideals in BCI-algebras are introduced.Conditions for an intuitionistic fuzzy ideal to be an intuitionistic fuzzy T-idealare provided. Using a collection of T-ideals, intuitionistic fuzzy T-ideals areestablished.
Simultaneous Triple Series Equations Involving Konhauser Biorthogonal Polynom...IOSR Journals
Biorthogonal polynomials are of great interest for Physicists.Spencer and Fano [9] used the biorthogonal polynomials (for the case k = 2) in carrying out calculations involving penetration of gamma rays through matter.In the present paper an exact solution of simultaneous triple series equations involving Konhauser-biorthogonal polynomials of first kind of different indices is obtained by multiplying factor technique due to Noble.[4] This technique has been modified by Thakare [10, 11] to solve dual series equations involving orthogonal polynomials which led to disprove a possible conjecture of Askey [1] that a dual series equation involving Jacobi polynomials of different indices can not be solved. In this paper the solution of simultaneous triple series equations involving generalized Laguerre polynomials also have been discussed as a charmfull particular case.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Some Common Fixed Point Results for Expansive Mappings in a Cone Metric SpaceIOSR Journals
The purpose of this work is to extend and generalize some common fixed point theorems for Expansive type mappings in complete cone metric spaces. We are attempting to generalize the several well- known recent results. Mathematical subject classification; 54H25, 47H10
Y.B.Jun et al. [9] introduced the notion of Cubic sets and Cubic subgroups. In this paper we introduced the
notion of cubic BF- Algebra i.e., an interval-valued BF-Algebra and an anti fuzzy BF-Algebra. Intersection of two cubic
BF- Algebras is again a cubic BF-Algebra is also studied.
Pseudo Bipolar Fuzzy Cosets of Bipolar Fuzzy and Bipolar Anti-Fuzzy HX Subgroupsmathsjournal
In this paper, we introduce the concept of pseudo bipolar fuzzy cosets, pseudo bipolar fuzzy double cosets of a bipolar fuzzy and bipolar anti-fuzzy subgroups. We also establish these concepts to bipolar fuzzy and bipolar anti-fuzzy HX subgroups of a HX group with suitable examples. Also we discuss some of their relative properties.
In this paper we introduce the notions of Fuzzy Ideals in BH-algebras and the notion
of fuzzy dot Ideals of BH-algebras and investigate some of their results.
Intuitionistic Fuzzification of T-Ideals in Bci-Algebrasiosrjce
The notions of intuitionistic fuzzy T-ideals in BCI-algebras are introduced.Conditions for an intuitionistic fuzzy ideal to be an intuitionistic fuzzy T-idealare provided. Using a collection of T-ideals, intuitionistic fuzzy T-ideals areestablished.
Simultaneous Triple Series Equations Involving Konhauser Biorthogonal Polynom...IOSR Journals
Biorthogonal polynomials are of great interest for Physicists.Spencer and Fano [9] used the biorthogonal polynomials (for the case k = 2) in carrying out calculations involving penetration of gamma rays through matter.In the present paper an exact solution of simultaneous triple series equations involving Konhauser-biorthogonal polynomials of first kind of different indices is obtained by multiplying factor technique due to Noble.[4] This technique has been modified by Thakare [10, 11] to solve dual series equations involving orthogonal polynomials which led to disprove a possible conjecture of Askey [1] that a dual series equation involving Jacobi polynomials of different indices can not be solved. In this paper the solution of simultaneous triple series equations involving generalized Laguerre polynomials also have been discussed as a charmfull particular case.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Some Common Fixed Point Results for Expansive Mappings in a Cone Metric SpaceIOSR Journals
The purpose of this work is to extend and generalize some common fixed point theorems for Expansive type mappings in complete cone metric spaces. We are attempting to generalize the several well- known recent results. Mathematical subject classification; 54H25, 47H10
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Matrix Transformations on Some Difference Sequence SpacesIOSR Journals
The sequence spaces 𝑙∞(𝑢,𝑣,Δ), 𝑐0(𝑢,𝑣,Δ) and 𝑐(𝑢,𝑣,Δ) were recently introduced. The matrix classes (𝑐 𝑢,𝑣,Δ :𝑐) and (𝑐 𝑢,𝑣,Δ :𝑙∞) were characterized. The object of this paper is to further determine the necessary and sufficient conditions on an infinite matrix to characterize the matrix classes (𝑐 𝑢,𝑣,Δ ∶𝑏𝑠) and (𝑐 𝑢,𝑣,Δ ∶ 𝑙𝑝). It is observed that the later characterizations are additions to the existing ones
Some Common Fixed Point Theorems for Multivalued Mappings in Two Metric SpacesIJMER
In this paper we prove some common fixed point theorems for multivalued mappings in two
complete metric spaces.
AMS Mathematics Subject Classification: 47H10, 54H25
In this paper we introduce the notions of Fuzzy Ideals in BH-algebras and the notion
of fuzzy dot Ideals of BH-algebras and investigate some of their results
In this paper, the notion α -anti fuzzy new-ideal of a PU-algebra are defined and discussed. The homomorphic images (pre images) ofα -anti fuzzy new-ideal under homomorphism of a PU-algebras has been obtained. Some related result have been derived.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Matrix Transformations on Some Difference Sequence SpacesIOSR Journals
The sequence spaces 𝑙∞(𝑢,𝑣,Δ), 𝑐0(𝑢,𝑣,Δ) and 𝑐(𝑢,𝑣,Δ) were recently introduced. The matrix classes (𝑐 𝑢,𝑣,Δ :𝑐) and (𝑐 𝑢,𝑣,Δ :𝑙∞) were characterized. The object of this paper is to further determine the necessary and sufficient conditions on an infinite matrix to characterize the matrix classes (𝑐 𝑢,𝑣,Δ ∶𝑏𝑠) and (𝑐 𝑢,𝑣,Δ ∶ 𝑙𝑝). It is observed that the later characterizations are additions to the existing ones
Some Common Fixed Point Theorems for Multivalued Mappings in Two Metric SpacesIJMER
In this paper we prove some common fixed point theorems for multivalued mappings in two
complete metric spaces.
AMS Mathematics Subject Classification: 47H10, 54H25
In this paper we introduce the notions of Fuzzy Ideals in BH-algebras and the notion
of fuzzy dot Ideals of BH-algebras and investigate some of their results
In this paper, the notion α -anti fuzzy new-ideal of a PU-algebra are defined and discussed. The homomorphic images (pre images) ofα -anti fuzzy new-ideal under homomorphism of a PU-algebras has been obtained. Some related result have been derived.
In this paper, the notion a -anti fuzzy new-ideal of a PU-algebra are defined and discussed. The
homomorphic images (pre images) ofa -anti fuzzy new-ideal under homomorphism of a PU-algebras has
been obtained. Some related result have been derived.
Pseudo Bipolar Fuzzy Cosets of Bipolar Fuzzy and Bipolar Anti-Fuzzy HX Subgroupsmathsjournal
In this paper, we introduce the concept of pseudo bipolar fuzzy cosets, pseudo bipolar fuzzy double cosets of a bipolar fuzzy and bipolar anti-fuzzy subgroups. We also establish these concepts to bipolar fuzzy and bipolar anti-fuzzy HX subgroups of a HX group with suitable examples. Also we discuss some of their relative properties.
Intuitionistic Fuzzy W- Closed Sets and Intuitionistic Fuzzy W -ContinuityWaqas Tariq
The aim of this paper is to introduce and study the concepts of intuitionistic fuzzy w- closed sets, intuitionistic fuzzy w-continuity and inttuitionistic fuzzy w-open & intuitionistic fuzzy w-closed mappings in intuitionistic fuzzy topological spaces.
In this paper, we introduce the concept of residual quotient of intuitionistic fuzzy subsets of ring and module and then define the notion of residual quotient intuitionistic fuzzy submodules , residual quotient intuitionistic fuzzy ideals. We study many properties of residual quotient relating to union, intersection, sum of intuitionistic fuzzy submodules (ideals). Using the concept of residual quotient, we investigate some important characterization of intuitionistic fuzzy annihilator of subsets of ring and module. We also study intuitionistic fuzzy prime submodules with the help of intuitionistic fuzzy annihilators. Many related properties are defined and discussed
In this paper, we introduce the concept of residual quotient of intuitionistic fuzzy subsets of ring and module and then define the notion of residual quotient intuitionistic fuzzy submodules , residual quotient intuitionistic fuzzy ideals. We study many properties of residual quotient relating to union, intersection, sum of intuitionistic fuzzy submodules (ideals). Using the concept of residual quotient, we investigate some important characterization of intuitionistic fuzzy annihilator of subsets of ring and module. We also study intuitionistic fuzzy prime submodules with the help of intuitionistic fuzzy annihilators. Many related properties are defined and discussed.
Similar to A Study on Intuitionistic Multi-Anti Fuzzy Subgroups (20)
OPTIMIZING SIMILARITY THRESHOLD FOR ABSTRACT SIMILARITY METRIC IN SPEECH DIAR...mathsjournal
Speaker diarization is a critical task in speech processing that aims to identify "who spoke when?" in an
audio or video recording that contains unknown amounts of speech from unknown speakers and unknown
number of speakers. Diarization has numerous applications in speech recognition, speaker identification,
and automatic captioning. Supervised and unsupervised algorithms are used to address speaker diarization
problems, but providing exhaustive labeling for the training dataset can become costly in supervised
learning, while accuracy can be compromised when using unsupervised approaches. This paper presents a
novel approach to speaker diarization, which defines loosely labeled data and employs x-vector embedding
and a formalized approach for threshold searching with a given abstract similarity metric to cluster
temporal segments into unique user segments. The proposed algorithm uses concepts of graph theory,
matrix algebra, and genetic algorithm to formulate and solve the optimization problem. Additionally, the
algorithm is applied to English, Spanish, and Chinese audios, and the performance is evaluated using wellknown similarity metrics. The results demonstrate that the robustness of the proposed approach. The
findings of this research have significant implications for speech processing, speaker identification
including those with tonal differences. The proposed method offers a practical and efficient solution for
speaker diarization in real-world scenarios where there are labeling time and cost constraints.
A POSSIBLE RESOLUTION TO HILBERT’S FIRST PROBLEM BY APPLYING CANTOR’S DIAGONA...mathsjournal
We present herein a new approach to the Continuum hypothesis CH. We will employ a string conditioning,
a technique that limits the range of a string over some of its sub-domains for forming subsets K of R. We
will prove that these are well defined and in fact proper subsets of R by making use of Cantor’s Diagonal
argument in its original form to establish the cardinality of K between that of (N,R) respectively
A Positive Integer 𝑵 Such That 𝒑𝒏 + 𝒑𝒏+𝟑 ~ 𝒑𝒏+𝟏 + 𝒑𝒏+𝟐 For All 𝒏 ≥ 𝑵mathsjournal
According to Bertrand's postulate, we have 𝑝𝑛 + 𝑝𝑛 ≥ 𝑝𝑛+1. Is it true that for all 𝑛 > 1 then 𝑝𝑛−1 + 𝑝𝑛 ≥𝑝𝑛+1? Then 𝑝𝑛 + 𝑝𝑛+3 > 𝑝𝑛+1 + 𝑝𝑛+2where 𝑛 ≥ 𝑁, 𝑁 is a large enough value?
A POSSIBLE RESOLUTION TO HILBERT’S FIRST PROBLEM BY APPLYING CANTOR’S DIAGONA...mathsjournal
We present herein a new approach to the Continuum hypothesis CH. We will employ a string conditioning,
a technique that limits the range of a string over some of its sub-domains for forming subsets K of R. We
will prove that these are well defined and in fact proper subsets of R by making use of Cantor’s Diagonal
argument in its original form to establish the cardinality of K between that of (N,R) respectively.
Moving Target Detection Using CA, SO and GO-CFAR detectors in Nonhomogeneous ...mathsjournal
systems in complex situations. A fundamental problem in radar systems is to automatically detect targets while maintaining a
desired constant false alarm probability. This work studies two detection approaches, the first with a fixed threshold and the
other with an adaptive one. In the latter, we have learned the three types of detectors CA, SO, and GO-CFAR. This research
aims to apply intelligent techniques to improve detection performance in a nonhomogeneous environment using standard
CFAR detectors. The objective is to maintain the false alarm probability and enhance target detection by combining
intelligent techniques. With these objectives in mind, implementing standard CFAR detectors is applied to nonhomogeneous
environment data. The primary focus is understanding the reason for the false detection when applying standard CFAR
detectors in a nonhomogeneous environment and how to avoid it using intelligent approaches.
OPTIMIZING SIMILARITY THRESHOLD FOR ABSTRACT SIMILARITY METRIC IN SPEECH DIAR...mathsjournal
Speaker diarization is a critical task in speech processing that aims to identify "who spoke when?" in an
audio or video recording that contains unknown amounts of speech from unknown speakers and unknown
number of speakers. Diarization has numerous applications in speech recognition, speaker identification,
and automatic captioning. Supervised and unsupervised algorithms are used to address speaker diarization
problems, but providing exhaustive labeling for the training dataset can become costly in supervised
learning, while accuracy can be compromised when using unsupervised approaches. This paper presents a
novel approach to speaker diarization, which defines loosely labeled data and employs x-vector embedding
and a formalized approach for threshold searching with a given abstract similarity metric to cluster
temporal segments into unique user segments. The proposed algorithm uses concepts of graph theory,
matrix algebra, and genetic algorithm to formulate and solve the optimization problem. Additionally, the
algorithm is applied to English, Spanish, and Chinese audios, and the performance is evaluated using wellknown similarity metrics. The results demonstrate that the robustness of the proposed approach. The
findings of this research have significant implications for speech processing, speaker identification
including those with tonal differences. The proposed method offers a practical and efficient solution for
speaker diarization in real-world scenarios where there are labeling time and cost constraints.
The Impact of Allee Effect on a Predator-Prey Model with Holling Type II Func...mathsjournal
There is currently much interest in predator–prey models across a variety of bioscientific disciplines. The focus is on quantifying predator–prey interactions, and this quantification is being formulated especially as regards climate change. In this article, a stability analysis is used to analyse the behaviour of a general two-species model with respect to the Allee effect (on the growth rate and nutrient limitation level of the prey population). We present a description of the local and non-local interaction stability of the model and detail the types of bifurcation which arise, proving that there is a Hopf bifurcation in the Allee effect module. A stable periodic oscillation was encountered which was due to the Allee effect on the
prey species. As a result of this, the positive equilibrium of the model could change from stable to unstable and then back to stable, as the strength of the Allee effect (or the ‘handling’ time taken by predators when predating) increased continuously from zero. Hopf bifurcation has arose yield some complex patterns that have not been observed previously in predator-prey models, and these, at the same time, reflect long term behaviours. These findings have significant implications for ecological studies, not least with respect to examining the mobility of the two species involved in the non-local domain using Turing instability. A spiral generated by local interaction (reflecting the instability that forms even when an infinitely large
carrying capacity is assumed) is used in the model.
A POSSIBLE RESOLUTION TO HILBERT’S FIRST PROBLEM BY APPLYING CANTOR’S DIAGONA...mathsjournal
We present herein a new approach to the Continuum hypothesis CH. We will employ a string conditioning,a technique that limits the range of a string over some of its sub-domains for forming subsets K of R. We will prove that these are well defined and in fact proper subsets of R by making use of Cantor’s Diagonal argument in its original form to establish the cardinality of K between that of (N,R) respectively.
Moving Target Detection Using CA, SO and GO-CFAR detectors in Nonhomogeneous ...mathsjournal
Modernization of radar technology and improved signal processing techniques are necessary to improve detection systems in complex situations. A fundamental problem in radar systems is to automatically detect targets while maintaining a
desired constant false alarm probability. This work studies two detection approaches, the first with a fixed threshold and the
other with an adaptive one. In the latter, we have learned the three types of detectors CA, SO, and GO-CFAR. This research
aims to apply intelligent techniques to improve detection performance in a nonhomogeneous environment using standard
CFAR detectors. The objective is to maintain the false alarm probability and enhance target detection by combining
intelligent techniques. With these objectives in mind, implementing standard CFAR detectors is applied to nonhomogeneous
environment data. The primary focus is understanding the reason for the false detection when applying standard CFAR
detectors in a nonhomogeneous environment and how to avoid it using intelligent approaches
OPTIMIZING SIMILARITY THRESHOLD FOR ABSTRACT SIMILARITY METRIC IN SPEECH DIAR...mathsjournal
Speaker diarization is a critical task in speech processing that aims to identify "who spoke when?" in an
audio or video recording that contains unknown amounts of speech from unknown speakers and unknown
number of speakers. Diarization has numerous applications in speech recognition, speaker identification,
and automatic captioning. Supervised and unsupervised algorithms are used to address speaker diarization
problems, but providing exhaustive labeling for the training dataset can become costly in supervised
learning, while accuracy can be compromised when using unsupervised approaches. This paper presents a
novel approach to speaker diarization, which defines loosely labeled data and employs x-vector embedding
and a formalized approach for threshold searching with a given abstract similarity metric to cluster
temporal segments into unique user segments. The proposed algorithm uses concepts of graph theory,
matrix algebra, and genetic algorithm to formulate and solve the optimization problem. Additionally, the
algorithm is applied to English, Spanish, and Chinese audios, and the performance is evaluated using wellknown similarity metrics. The results demonstrate that the robustness of the proposed approach. The
findings of this research have significant implications for speech processing, speaker identification
including those with tonal differences. The proposed method offers a practical and efficient solution for
speaker diarization in real-world scenarios where there are labeling time and cost constraints
Modified Alpha-Rooting Color Image Enhancement Method on the Two Side 2-D Qua...mathsjournal
Color in an image is resolved to 3 or 4 color components and 2-Dimages of these components are stored in separate channels. Most of the color image enhancement algorithms are applied channel-by-channel on each image. But such a system of color image processing is not processing the original color. When a color image is represented as a quaternion image, processing is done in original colors. This paper proposes an implementation of the quaternion approach of enhancement algorithm for enhancing color images and is referred as the modified alpha-rooting by the two-dimensional quaternion discrete Fourier transform (2-D QDFT). Enhancement results of this proposed method are compared with the channel-by-channel image enhancement by the 2-D DFT. Enhancements in color images are quantitatively measured by the color enhancement measure estimation (CEME), which allows for selecting optimum parameters for processing by thegenetic algorithm. Enhancement of color images by the quaternion based method allows for obtaining images which are closer to the genuine representation of the real original color.
An Application of Assignment Problem in Laptop Selection Problem Using MATLABmathsjournal
The assignment – selection problem used to find one-to- one match of given “Users” to “Laptops”, the main objective is to minimize the cost as per user requirement. This paper presents satisfactory solution for real assignment – Laptop selection problem using MATLAB coding.
The aim of this paper is to study the class of β-normal spaces. The relationships among s-normal spaces, pnormal spaces and β-normal spaces are investigated. Moreover, we study the forms of generalized β-closed
functions. We obtain characterizations of β-normal spaces, properties of the forms of generalized β-closed
functions and preservation theorems.
Cubic Response Surface Designs Using Bibd in Four Dimensionsmathsjournal
Response Surface Methodology (RSM) has applications in Chemical, Physical, Meteorological, Industrial and Biological fields. The estimation of slope response surface occurs frequently in practical situations for the experimenter. The rates of change of the response surface, like rates of change in the yield of crop to various fertilizers, to estimate the rates of change in chemical experiments etc. are of
interest. If the fit of second order response is inadequate for the design points, we continue the
experiment so as to fit a third order response surface. Higher order response surface designs are sometimes needed in Industrial and Meteorological applications. Gardiner et al (1959) introduced third order rotatable designs for exploring response surface. Anjaneyulu et al (1994-1995) constructed third order slope rotatable designs using doubly balanced incomplete block designs. Anjaneyulu et al (2001)
introduced third order slope rotatable designs using central composite type design points. Seshu babu et al (2011) studied modified construction of third order slope rotatable designs using central composite
designs. Seshu babu et al (2014) constructed TOSRD using BIBD. In view of wide applicability of third
order models in RSM and importance of slope rotatability, we introduce A Cubic Slope Rotatable Designs Using BIBD in four dimensions.
The caustic that occur in geodesics in space-times which are solutions to the gravitational field equations with the energy-momentum tensor satisfying the dominant energy condition can be circumvented if quantum variations are allowed. An action is developed such that the variation yields the field equations
and the geodesic condition, and its quantization provides a method for determining the extent of the wave packet around the classical path.
Approximate Analytical Solution of Non-Linear Boussinesq Equation for the Uns...mathsjournal
For one dimensional homogeneous, isotropic aquifer, without accretion the governing Boussinesq equation under Dupuit assumptions is a nonlinear partial differential equation. In the present paper approximate analytical solution of nonlinear Boussinesq equation is obtained using Homotopy perturbation transform method(HPTM). The solution is compared with the exact solution. The comparison shows that the HPTM is efficient, accurate and reliable. The analysis of two important aquifer
parameters namely viz. specific yield and hydraulic conductivity is studied to see the effects on the height of water table. The results resemble well with the physical phenomena.
Common Fixed Point Theorems in Compatible Mappings of Type (P*) of Generalize...mathsjournal
In this paper, we give some new definition of Compatible mappings of type (P), type (P-1) and type (P-2) in intuitionistic generalized fuzzy metric spaces and prove Common fixed point theorems for six mappings
under the conditions of compatible mappings of type (P-1) and type (P-2) in complete intuitionistic fuzzy
metric spaces. Our results intuitionistically fuzzify the result of Muthuraj and Pandiselvi [15]
Mathematics subject classifications: 45H10, 54H25
A Probabilistic Algorithm for Computation of Polynomial Greatest Common with ...mathsjournal
In the earlier work, Knuth present an algorithm to decrease the coefficient growth in the Euclidean algorithm of polynomials called subresultant algorithm. However, the output polynomials may have a small factor which can be removed. Then later, Brown of Bell Telephone Laboratories showed the subresultant in another way by adding a variant called 𝜏 and gave a way to compute the variant. Nevertheless, the way failed to determine every 𝜏 correctly.
In this paper, we will give a probabilistic algorithm to determine the variant 𝜏 correctly in most cases by adding a few steps instead of computing 𝑡(𝑥) when given 𝑓(𝑥) and𝑔(𝑥) ∈ ℤ[𝑥], where 𝑡(𝑥) satisfies that 𝑠(𝑥)𝑓(𝑥) + 𝑡(𝑥)𝑔(𝑥) = 𝑟(𝑥), here 𝑡(𝑥), 𝑠(𝑥) ∈ ℤ[𝑥]
Table of Contents - September 2022, Volume 9, Number 2/3mathsjournal
Applied Mathematics and Sciences: An International Journal (MathSJ ) aims to publish original research papers and survey articles on all areas of pure mathematics, theoretical applied mathematics, mathematical physics, theoretical mechanics, probability and mathematical statistics, and theoretical biology. All articles are fully refereed and are judged by their contribution to advancing the state of the science of mathematics.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
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A Study on Intuitionistic Multi-Anti Fuzzy Subgroups
1. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 2, August 2014
35
A Study on Intuitionistic Multi-Anti Fuzzy Subgroups
R.Muthuraj 1
, S.Balamurugan 2
1
PG and Research Department of Mathematics,H.H. The Rajah’s College,
Pudukkotta622 001,Tamilnadu, India.
2
Department of Mathematics,Velammal College of Engineering & Technology,
Madurai-625 009,Tamilnadu, India.
ABSTRACT
For any intuitionistic multi-fuzzy set A = { < x , µA(x) , νA(x) > : x∈X} of an universe set X, we
study the set [A](α, β) called the (α, β)–lower cut of A. It is the crisp multi-set { x∈X : µi(x) ≤ αi ,
νi(x) ≥ βi , ∀i } of X. In this paper, an attempt has been made to study some algebraic structure
of intuitionistic multi-anti fuzzy subgroups and their properties with the help of their (α, β)–lower
cut sets.
Keywords
Intuitionistic fuzzy set (IFS), Intuitionistic multi-fuzzy set (IMFS), Intuitionistic multi-anti fuzzy
subgroup (IMAFSG), Intuitionistic multi-anti fuzzy normal subgroup (IMAFNSG), ( , )–lower
cut, Homomorphism.
Mathematics Subject Classification 20N25, 03E72, 08A72, 03F55, 06F35, 03G25, 08A05,
08A30.
1. INTRODUCTION
After the introduction of the concept of fuzzy set by Zadeh [14] several researches were
conducted on the generalization of the notion of fuzzy set. The idea of Intuitionistic fuzzy set was
given by Krassimir.T.Atanassov [1]. An Intuitionistic Fuzzy set is characterized by two functions
expressing the degree of membership (belongingness) and the degree of non-membership (non-
belongingness) of elements of the universe to the IFS. Among the various notions of higher-order
fuzzy sets, Intuitionistic Fuzzy sets proposed by Atanassov provide a flexible framework to
explain uncertainity and vagueness. An element of a multi-fuzzy set can occur more than once
with possibly the same or different membership values. In this paper we study Intuitionistic
multi-anti fuzzy subgroup with the help of some properties of their (α, β)–lower cut sets. This
paper is an attempt to combine the two concepts: Intuitionistic Fuzzy sets and Multi-fuzzy sets
together by introducing two new concepts called Intuitionistic Multi-fuzzy sets and Intuitionistic
Multi-Anti fuzzy subgroups.
2. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 2, August 2014
36
2. PRELIMINARIES
In this section, we site the fundamental definitions that will be used in the sequel.
2.1 Definition [14]
Let X be a non-empty set. Then a fuzzy set µ : X → [0,1].
2.2 Definition [9]
Let X be a non-empty set. A multi-fuzzy set A of X is defined as A = { < x, µA(x) > : x∈X }
where µA = ( µ1, µ2, … , µk ) , that is, µA(x) = ( µ1(x), µ2(x), … , µk(x) ) and µi : X → [0,1] ,
∀i=1,2,…,k. Here k is the finite dimension of A. Also note that, for all i, µi(x) is a decreasingly
ordered sequence of elements. That is, µ1(x) ≥ µ2(x) ≥ … ≥µk(x) ,∀x∈X.
2.3 Definition [1]
Let X be a non-empty set. An Intuitionistic Fuzzy Set (IFS) A of X is an object of the form A =
{< x, µ(x), ν(x) > : x∈X}, where µ : X → [0, 1] and ν : X → [0, 1] define the degree of
membership and the degree of non-membership of the element x∈X respectively with 0 ≤ µ(x) +
ν(x) ≤ 1, ∀x∈X.
2.4 Remark [1]
(i) Every fuzzy set A on a non-empty set X is obviously an intuitionistic fuzzy set
having the form A = {< x, µ(x), 1−µ(x) > : x∈X}.
(ii) In the definition 2.3, When µ(x) + ν(x) = 1, that is, when ν(x) = 1−µ(x) = µc
(x), A is
called fuzzy set.
2.5 Definition [13]
Let A = {< x, µA(x), νA(x) > : x∈X } where µA(x) = ( µ1(x), µ2(x), … , µk(x) ) and νA(x) = ( ν1(x),
ν2(x), … , νk(x) ) such that 0 ≤ µi(x) + νi(x) ≤ 1, for all i, ∀x∈X. Here, µ1(x) ≥ µ2(x) ≥ … ≥ µk(x) ,
∀x∈X. That is, µi 's are decreasingly ordered sequence. That is, 0 ≤ µi(x) + νi(x) ≤ 1,∀x∈X, for
i=1, 2, … , k. Then the set A is said to be an Intuitionistic Multi-Fuzzy Set (IMFS) with
dimension k of X.
2.6 Remark [13]
Note that since we arrange the membership sequence in decreasing order, the
corresponding non-membership sequence may not be in decreasing or increasing order.
2.7 Definition [13]
Let A = { < x , µA(x), νA(x) > : x∈X } and B = { < x , µB(x), νB(x) > : x∈X } be any two
IMFS’s having the same dimension k of X. Then
(i) A ⊆ B if and only if µA(x) ≤ µB(x) and νA(x) ≥ νB(x) for all x∈X.
3. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 2, August 2014
37
(ii) A = B if and only if µA(x) = µB(x) and νA(x) = νB(x) for all x∈X.
(iii) ¬A = { < x , νA(x), µA(x) > : x∈X }
(iv) A ∩ B = { < x , (µA∩ B)(x), (νA∩B)(x) > : x∈X }, where
(µA∩B)(x) = min{ µA(x), µB(x) } = ( min{µiA(x), µiB(x)} )k
i=1 and
(νA∩B)(x) = max{ νA(x), νB(x) } = ( max{νiA(x), νiB(x)} )k
i=1
(v) A ∪ B = { < x , (µA∪B)(x), (νA∪B)(x) > : x∈X }, where
(µA∪B)(x) = max{ µA(x), µB(x) } = ( max{µiA(x), µiB(x)} )k
i=1 and
(νA∪B)(x) = min{ νA(x), νB(x) } = ( min{νiA(x), νiB(x)} )k
i=1
Here { µiA(x), µiB(x) } represents the corresponding ith
position membership values of A and B
respectively. Also { νiA(x), νiB(x) } represents the corresponding ith
position non-membership
values of A and B respectively.
2.8 Theorem [13]
For any three IMFS’s A, B and C , we have :
1. Commutative Law
A∪B = B∪A
A∩B = B∩A
2. Idempotent Law
A∪A=A
A∩A=A
3. De Morgan's Laws
¬(A∪B) = (¬A∩¬B)
¬(A∩B) = (¬A∪¬B)
4. Associative Law
A∪(B∪C) = (A∪B)∪C
A∩(B∩C) = (A∩B)∩C
5. Distributive Law
A∪(B∩C) = (A∪B)∩(A∪C)
A∩(B∪C) = (A∩B)∪(A∩C)
2.9 Definition
Let A = { < x , µA(x), νA(x) > : x∈X } be an IMFS and let α = (α1,α2, … ,αk)∈[0,1]k
and β =
(β1,β2, … , βk)∈[0,1]k
, where each αi , βi∈[0,1] with 0 ≤ αi + βi ≤ 1,∀i. Then (αααα, ββββ)-lower cut of
A is the set of all x such that µi(x) ≤ αi with the corresponding νi(x) ≥ βi ,∀i and is denoted by
[A](α, β). Clearly it is a crisp multi-set.
2.10 Definition
Let A = { < x, µA(x), νA(x) > : x∈X } be an IMFS and let α = (α1,α2, … ,αk)∈[0,1]k
and β =
4. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 2, August 2014
38
(β1,β2, … , βk)∈[0,1]k
, where each αi , βi∈[0,1] with 0 ≤ αi + βi ≤ 1,∀i. Then strong (αααα, ββββ)-lower
cut of A is the set of all x such that µi(x) < αi with the corresponding νi(x) > βi ,∀i and is denoted
by [A](α, β)* . Clearly it is also a crisp multi-set.
The following Theorem is an immediate consequence of the above definitions.
2.11 Theorem [13]
Let A and B are any two IMFS’s of dimension k drawn from a set X. Then A ⊆ B if and only if
[B](α ,β) ⊆ [A](α ,β) for every α, β∈[0,1]k
with 0 ≤ αi + βi ≤ 1 for all i.
2.12 Definition
An intuitionistic multi-fuzzy set ( In short IMFS) A = { < x , µA(x), νA(x) > : x∈G } of a group G
is said to be an intuitionistic multi-anti fuzzy subgroup of G ( In short IMAFSG ) if it satisfies
the following : For all x,y∈G,
(i) µA(xy) ≤ max {µA(x), µA(y)}
(ii) µA(x-1
) = µA(x)
(iii) νA(xy) ≥ min {νA(x), νA(y)}
(iv) νA(x-1
) = νA(x)
2.13 Definition
An intuitionistic multi-fuzzy set (In short IMFS) A = { < x, µA(x), νA(x) > : x∈G } of a group G
is said to be an intuitionistic multi-anti fuzzy subgroup of G (In short IMAFSG) if it satisfies :
(i) µA(xy-1
) ≤ max{µA(x), µA(y)} and
(ii) νA(xy-1
) ≥ min{νA(x), νA(y)} ,∀x,y∈G
2.13.1 Remark
(i) If A is an IFS of a group G, then we can not say about the complement of A,
because it is not an IFS of G.
(ii) If A is an IAFSG of a group G, then Ac
is need not be an IFS of G.
(iii) A is an IMAFSG of a group G ⇔ each IFS { < x, µiA(x), νiA(x) : x∈G > }i=1
k
is
an IAFSG of G.
(iv) If A is an IMAFSG of a group G, then in general, we can not say Ac
is an IMFSG
of the group G.
2.14 Definition
An IMAFSG A = { < x, µA(x), νA(x) > : x∈G } of a group G is said to be an intuitionistic multi-
anti fuzzy normal subgroup ( In short IMAFNSG ) of G if it satisfies :
(i) µA(xy) = µA(yx) and
(ii) νA(xy) = νA(yx) , for all x,y∈G
5. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 2, August 2014
39
2.15 Theorem
An intuitionistic multi-anti fuzzy subgroup (IMAFSG) A of a group G is said to be normal if it
satisfies :
(i) µA(g-1
xg) = µA(x) and
(ii) νA(g-1
xg) = νA(x) , for all x∈A and g∈G
Proof Let x∈A and g∈G be any element.
Then µA(g-1
xg) = µA(g-1
(xg)) = µA((xg)g-1
), since A is normal.
= µA(x(gg-1
)) = µA(xe) = µA(x). Hence the proof (i).
Now, νA(g-1
xg) = νA(g-1
(xg)) = νA((xg)g-1
) , since A is normal.
= νA(x(gg-1
)) = νA(xe) = νA(x). Hence the proof (ii).
2.16 Definition
Let (G, .) be a groupoid and A, B be any two IMFS’s having same dimension k of G. Then the
product of A and B is denoted by A◦B and it is defined as :
∀x∈G, A◦B(x) = ( µA◦B(x), νA◦B(x) ) where
max [min{µA(y), µB(z)}: yz=x , ∀y,z∈G]
µA◦B(x) =
0k=(0, 0, … , k times) , if x is not expressible as x=yz and
min [max{νA(y), νB(z)}:yz=x , ∀y,z∈G]
νA◦B(x) =
1k=(1, 1, … , k times) , if x is not expressible as x=yz
That is, ∀x∈G,
( max[min{µA(y), µB(z)}:yz=x,∀y,z∈G], min[max{νA(y), νB(z)}:yz=x,∀y,z∈G] )
A◦B(x) =
(0k,1k), if x is not expressible as x=yz
That is, ∀x∈G,
(max[min{µiA(y),µiB(z)}:yz=x,∀y,z∈G],min[max{νiA(y),νiB(z)}:yz=x,∀y,z∈G])k
i=1
A◦B(x) =
(0,1)k ,if x is not expressible as x=yz where (0,1)k=((0,1), (0,1), … , k times)
6. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 2, August 2014
40
2.17 Definition
Let X and Y be any two non-empty sets and f : X → Y be a mapping. Let A and B be any two
IMFS’s having same dimension k, of X and Y respectively. Then the image of A(⊆X) under the
map f is denoted by f(A) and it is defined as :
∀y∈Y, f(A)(y) = ( µf(A)(y), νf(A)(y) ) where
max{µA(x) : x∈f-1
(y)}
µf(A)(y) =
0k , otherwise and
min{νA(x) : x∈f-1
(y)}
νf(A)(y) =
1k , otherwise
( max{µiA(x) : x∈f-1
(y)}, min{νiA(x) : x∈f-1
(y)} )k
i=1
That is, f(A)(y) =
(0,1)k , otherwise where (0,1)k=( (0,1), (0,1), … , k times )
Also, the pre-image of B(⊆Y) under the map f is denoted by f-1
(B) and it is defined as :
∀x∈X, f-1
(B)(x) = ( µB(f(x)), νB(f(x)) )
3. PROPERTIES OF (α, β) –LOWER CUT OF INTUITIONISTIC
MULTI-FUZZY SET
In this section we shall prove some theorems on intuitionistic multi-anti fuzzy subgroups of a
group G with the help of their (α, β) –lower cuts.
3.1 Proposition
If A and B are any two IMFS’s of a universal set X, then their (α, β) –lower cuts satisfies the
following :
(i) [A](α, β) ⊆ [A](δ, θ) if α ≤ δ and β ≥ θ
(ii) A ⊆ B implies [B](α, β) ⊆ [A](α, β)
(iii) [A∩B](α, β) = [A](α, β) ∩ [B](α, β)
(iv) [A∪B](α, β) ⊆ [A](α, β) ∪ [B](α, β) (Here equality holds if αi + βi = 1, ∀i )
(v) [∩Ai ](α, β) = ∩ [Ai ](α, β) ,where α, β, δ, θ∈[0,1]k
3.2 Proposition
Let (G, .) be a groupoid and A, B be any two IMFS’s of G. Then we have [A◦B](α, β) = [A](α, β)
[B](α, β) where α, β∈[0,1]k
.
3.3 Theorem
7. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 2, August 2014
41
If A is an intuitionistic multi-anti fuzzy subgroup of a group G and α, β∈[0,1]k
, then the (α, β)-
lower cut of A, [A](α, β) is a subgroup of G, where µA(e) ≤ α , νA(e) ≥ β and ‘e’ is the identity
element of G.
Proof since µA(e) ≤ α and νA(e) ≥ β , e∈[A](α, β) . Therefore, [A](α, β) ≠ φ.
Let x,y∈[A](α, β) . Then µA(x) ≤ α , νA(x) ≥ β and µA(y) ≤ α , νA(y) ≥ β.
Then ∀i, µiA(x) ≤ αi , νiA(x) ≥ βi and µiA(y) ≤ αi , νiA(y) ≥ βi .
⇒ max{µiA(x), µiA(y)} ≤ αi and min{νiA(x), νiA(y)} ≥ βi ,∀i……………(1)
⇒ µiA(xy-1
) ≤ max{µiA(x), µiA(y)} ≤ αi and νiA(xy-1
) ≥ min{νiA(x), νiA(y)} ≥ βi ,∀i, since
A is an intuitionistic multi-anti fuzzy subgroup of a group G and by (1).
⇒ µiA(xy-1
) ≤ αi and νiA(xy-1
) ≥ βi ,∀i.
⇒ µA(xy-1
) ≤ α and νA(xy-1
) ≥ β
⇒ xy-1
∈[A](α, β)
⇒ [A](α, β) is a subgroup of G.
Hence the Theorem.
3.4 Theorem
The IMFS A is an intuitionistic multi-anti fuzzy subgroup of a group G ⇔ each (α,β)-lower cut
[A](α, β) is a subgroup of G, ∀ α, β∈[0, 1]k
.
Proof From the above Theorem 3.3, it is clear.
3.5 Theorem
If A is an intuitionistic multi-anti fuzzy normal subgroup of a group G and α, β∈[0, 1]k
, then
(α,β)-lower cut [A](α, β) is a normal subgroup of G, where µA(e) ≤ α , νA(e) ≥ β and ‘e’ is the
identity element of G.
Proof Let x∈[A](α, β) and g∈G. Then µA(x) ≤ α and νA(x) ≥ β.
That is, µiA(x) ≤ αi and νiA(x) ≥ βi ∀i ……….(1)
Since A is an intuitionistic multi-anti fuzzy normal subgroup of G,
µiA(g-1
xg) = µiA(x) and νiA(g-1
xg) = νiA(x), ∀i.
⇒ µiA(g-1
xg) = µiA(x) ≤ αi and νiA(g-1
xg) = νiA(x) ≥ βi ,∀i, by using(1).
⇒ µiA(g-1
xg) ≤ αi and νiA(g-1
xg) ≥ βi ,∀i.
⇒ µA(g-1
xg) ≤ α and νA(g-1
xg) ≥ β
⇒ g-1
xg∈[A](α, β)
⇒ [A](α, β) is a normal subgroup of G.
Hence the Theorem.
3.6 Theorem
If A is an intuitionistic multi-fuzzy subset of a group G, then A is an
intuitionistic multi-anti fuzzy subgroup of G ⇔ each (α, β)-lower cut [A](α, β) is a subgroup of
G ,for all α, β∈[0,1]k
with αi + βi ≤ 1, ∀i.
8. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 2, August 2014
42
Proof ⇒⇒⇒⇒ Let A be an intuitionistic multi-anti fuzzy subgroup of a group G. Then by the
Theorem 3.4, each (α, β)-lower cut [A](α, β) is a subgroup of G for all α, β∈[0,1]k
with αi + βi ≤
1, ∀i.
⇐⇐⇐⇐ Conversely, let A be an intuitionistic multi-fuzzy subset of a group G such that each
(α, β)-lower cut [A](α, β) is a subgroup of G for all α, β∈[0,1]k
with αi + βi ≤ 1, ∀i.
To prove that A is an intuitionistic multi-anti fuzzy subgroup of G, we prove :
(i) µA(xy) ≤ max{µA(x), µA(y)} and νA(xy) ≥ min{νA(x), νA(y)} for all x,y∈G
(ii) µA(x-1
) = µA(x) and νA(x-1
) = νA(x)
For proof (i): Let x,y∈G and for all i,
let αi = max{µiA(x), µiA(y)} and βi = min{νiA(x), νiA(y)}.
Then ∀i, we have µiA(x) ≤ αi , µiA(y) ≤ αi and νiA(x) ≥ βi , νiA(y) ≥ βi
That is, ∀i, we have µiA(x) ≤ αi , νiA(x) ≥ βi and µiA(y) ≤ αi , νiA(y) ≥ βi
Then we have µA(x) ≤ α , νA(x) ≥ β and µA(y) ≤ α , νA(y) ≥ β
That is, x∈[A](α, β) and y∈[A](α, β)
Therefore, xy∈[A](α, β) , since each (α, β)-lower cut [A](α, β) is a subgroup by hypothesis.
Therefore, ∀i, we have µiA(xy) ≤ αi = max{µiA(x), µiA(y)} and
νiA(xy) ≥ βi = min{νiA(x), νiA(y)}.
That is, µA(xy) ≤ max{µA(x), µA(y)} and νA(xy) ≥ min{νA(x), νA(y)} and hence (i).
For proof (ii): Let x∈G and ∀i, let µiA(x) = αi and νiA(x) = βi .
Then µiA(x) ≤ αi and νiA(x) ≥ βi is true ∀i.
Therefore, µA(x) ≤ α and νA(x) ≥ β
Therefore, x∈[A](α, β) .
Since each (α, β)-lower cut [A](α, β) is a subgroup of G for all α, β∈[0,1]k
and x∈[A](α, β)
,we have
x-1
∈[A](α, β) which implies that µiA(x-1
) ≤ αi and νiA(x-1
) ≥ βi is true ∀i.
⇒ µiA(x-1
) ≤ µiA(x) and νiA(x-1
) ≥ νiA(x) is true ∀i.
Thus, ∀i, µiA(x)= µiA((x-1
)-1
) ≤ µiA(x-1
) ≤ µiA(x) which implies that µiA(x-1
) = µiA(x) ,∀i
and hence µA(x-1
) = µA(x).
9. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 2, August 2014
43
And ∀i, νiA(x)= νiA((x-1
)-1
) ≥ νiA(x-1
) ≥ νiA(x) which implies that νiA(x-1
) = νiA(x) ,∀i and
hence νA(x-1
) = νA(x).
Hence A is an intuitionistic multi-anti fuzzy subgroup of G and hence the Theorem.
3.7 Theorem
If A and B are any two intuitionistic multi-anti fuzzy subgroups (IMAFSG’s) of a group
G, then (A∪B) is an intuitionistic multi-anti fuzzy subgroup of G.
Proof since A and B are IMAFSG’s of G, we have ∀x,y∈G,
(i) µA(xy-1
) ≤ max{µA(x), µA(y)} and νA(xy-1
) ≥ min{νA(x), νA(y)}
(ii) µB(xy-1
) ≤ max{µB(x), µB(y)} and νB(xy-1
) ≥ min{νB(x), νB(y)} …….(1)
Now A∪B = { < x, µA∪B(x), νA∪B(x) > : x∈G } where µA∪B(x) = max{ µA(x), µB(x) } and
νA∪B(x) = min { νA(x), νB(x) }.
Then µA∪B(xy-1
) = max{ µA(xy-1
), µB(xy-1
) }
≤ max{ max{µA(x), µA(y)}, max{µB(x), µB(y)} }, by using (1)
= max{ max{µA(x), µB(x)}, max{µA(y), µB(y)} }
= max{ µA∪B(x), µA∪B(y) }
and νA∪B(xy-1
) = min{ νA(xy-1
), νB(xy-1
) }
≥ min{ min{νA(x), νA(y)}, min{νB(x), νB(y)} } , by using (1)
= min{ min{νA(x), νB(x)}, min{νA(y), νB(y)} }
= min{ νA∪B(x), νA∪B(y) }
That is, µA∪B(xy-1
) ≤ max{ µA∪B(x), µA∪B(y) } and νA∪B(xy-1
) ≥ min{ νA∪B(x), νA∪B(y) },
∀x,y∈G.
Hence (A∪B) is an intuitionistic multi-anti fuzzy subgroup of G.
Hence the Theorem.
3.8 Theorem
The intersection of any two IMAFSG’s of a group G need not be an IMAFSG of G.
Proof Consider the abelian group G = { e, a, b, ab } with usual multiplication such that a2
= e =
b2
and ab = ba. Let A = { < e, (0.2, 0.2), (0.7, 0.8) >, < a, (0.5, 0.5), (0.4, 0.4) >, < b, (0.5, 0.5),
(0.2, 0.4) >, < ab, (0.4, 0.5), (0.2, 0.4) > } and B = { < e, (0.3, 0.1), (0.7, 0.8) >, < a, (0.8, 0.4),
(0.2, 0.6) >, < b, (0.6, 0.4), (0.4, 0.5) >, < ab, (0.8, 0.4), (0.2, 0.5) > } be two IMFS’s having
dimension two of the group G. Clearly A and B are IMAFSG’s of G.
Then A∩B = { < e, (0.2, 0.1), (0.7, 0.8) >, < a, (0.5, 0.4), (0.4, 0.6) >, < b, (0.5, 0.4), (0.4, 0.5)
>, < ab, (0.4, 0.4), (0.2, 0.5) > }. Here, it is easily verify that A∩B is not an IMAFSG of G.
Hence the Theorem.
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3.9 Theorem
Let A and B be an IMAFSG’s of a group G. But it is an uncertain to verify that A∩B is an
IMAFSG of G.
Proof This proof is done by the following two examples that are discussed in two cases : case(i)
and case(ii).
Case (i) : A and B are IMAFSG’s of a group G ⇒ A∪B is an IMAFSG of G but A∩B
is not an IMAFSG of the group G.
Consider the abelian group G = { e, a, b, ab } with usual multiplication such that a2
= e =
b2
and ab = ba. Let A = { < e, (0.2, 0.2), (0.7, 0.8) >, < a, (0.5, 0.5), (0.4, 0.4) >, < b, (0.5, 0.5),
(0.2, 0.4) >, < ab, (0.4, 0.5), (0.2, 0.4) > } and B = { < e, (0.3, 0.1), (0.7, 0.8) >, < a, (0.8, 0.4),
(0.2, 0.6) >, < b, (0.6, 0.4), (0.4, 0.5) >, < ab, (0.8, 0.4), (0.2, 0.5) > } be two IMFS’s having
dimension two of the group G. Clearly A and B are IMAFSG’s of G.
Then A∪B = { < e, (0.3, 0.2), (0.7, 0.8) >, < a, (0.8, 0.5), (0.2, 0.4) >, < b, (0.6, 0.5), (0.2, 0.4)
>, < ab, (0.8, 0.5), (0.2, 0.4) > } and A∩B = { < e, (0.2, 0.1), (0.7, 0.8) >, < a, (0.5, 0.4), (0.4,
0.6) >, < b, (0.5, 0.4), (0.4, 0.5) >, < ab, (0.4, 0.4), (0.2, 0.5) > }.
Here, it is easily verify that A∪B is an IMAFSG of G but A∩B is not an IMAFSG of G.
Hence case (i).
Case (ii) : A and B are IMAFSG’s of a group G ⇒ both A∪B and A∩B are IMAFSG’s
of the group G.
Consider the abelian group G = { e, a, b, ab } with usual multiplication such that a2
= e =
b2
and ab = ba. Let A = { < e, (0.2, 0.1), (0.8, 0.8) >, < a, (0.5, 0.4), (0.4, 0.6) >, < b, (0.5, 0.4),
(0.4, 0.5) >, < ab, (0.5, 0.4), (0.4, 0.5) > } and B = { < e, (0.3, 0.2), (0.7, 0.7) >, < a, (0.8, 0.5),
(0.2, 0.4) >, < b, (0.6, 0.5), (0.4, 0.2) >, < ab, (0.8, 0.4), (0.2, 0.2) > } be two IMFS’s having
dimension two of the group G. Clearly A and B are IMAFSG’s of G.
Then A∪B = { < e, (0.3, 0.2), (0.7, 0.7) >, < a, (0.8, 0.5), (0.2, 0.4) >, < b, (0.6, 0.5), (0.4, 0.2)
>, < ab, (0.8, 0.4), (0.2, 0.2) > } and A∩B = { < e, (0.2, 0.1), (0.8, 0.8) >, < a, (0.5, 0.4), (0.4,
0.6) >, < b, (0.5, 0.4), (0.4, 0.5) >, < ab, (0.5, 0.4), (0.4, 0.5) > }.
Here, it is easily to verify that both A∪B and A∩B are IMAFSG’s of G. Hence case (ii).
From case (i) and case (ii), clearly it is an uncertain to verify that A∩B is an IMAFSG of G.
Hence the Theorem.
3.10 Theorem
Let A and B be any two IMAFSG’s of a group G. Then A◦B is an IMAFSG of G ⇔ A◦B=B◦A
Proof Since A and B are IMAFSG’s of G, each (α, β)-lower cuts [A](α, β) and [B](α, β) are
subgroups of G, ∀α,β∈[0,1]k
with αi + βi ≤ 1, ∀i ………………(1)
Suppose A◦B is an IMAFSG of G.
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45
⇔ each (α, β)-lower cuts [A◦B](α, β) are subgroups of G, ∀α,β∈[0,1]k
with αi + βi ≤ 1, ∀i.
Now, from (1), [A](α, β) [B](α, β) is a subgroup of G ⇔ [A](α, β) [B](α, β) = [B](α, β) [A](α, β) ,since if
H and K are any two subgroups of G, then HK is a subgroup of G ⇔ HK=KH.
⇔ [A◦B](α, β) = [B◦A](α, β) , ∀α,β∈[0,1]k
with αi + βi ≤ 1, ∀i.
⇔ A◦B = B◦A
Hence the Theorem.
3.11 Theorem
If A is any IMAFSG of a group G, then A◦A = A .
Proof Since A is an IMAFSG of a group G,
each (α, β)-lower cut [A](α, β) is a subgroup of G, ∀α,β∈[0,1]k
with αi + βi ≤ 1, ∀i.
⇒ [A](α, β)[A](α, β) = [A](α, β) , since H is a subgroup of G ⇒ HH = H.
⇒ [A◦A](α, β) = [A](α, β) , ∀α,β∈[0,1]k
with αi + βi ≤ 1, ∀i.
⇒ A◦A = A
Hence the Theorem.
4. INTUITIONISTIC MULTI-FUZZY COSETS
In this section we shall prove some theorems on intuitionistic multi-fuzzy cosets of a group
G.
4.1 Definition
Let G be a group and A be an IMAFSG of G. Let x∈G be a fixed element. Then the set
xA = {( g, µxA(g), νxA(g) ) : g∈G } where µxA(g) = µA(x-1
g) and νxA(g) = νA(x-1
g), ∀g∈G is
called the intuitionistic multi-fuzzy left coset of G determined by A and x.
Similarly, the set Ax = { ( g, µAx(g), νAx(g) ) : g∈G } where µAx(g) = µA(gx-1
) and νAx(g) =
νA(gx-1
),∀g∈G is called the intuitionistic multi-fuzzy right coset of G determined by A and x.
4.2 Remark
It is clear that if A is an intuitionistic multi-anti fuzzy normal subgroup of G, then the
intuitionistic multi-fuzzy left coset and the intuitionistic multi-fuzzy right coset of A on G
coincides and in this case, we simply call it as intuitionistic multi-fuzzy coset.
4.3 Example
Let G be a group. Then A = { < x, µA(x), νA(x) >, x∈G / µA(x) = µA(e) and νA(x) = νA(e) } is an
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46
intuitionistic multi-anti fuzzy normal subgroup of G.
Proof It is easy to verify.
4.4 Theorem
Let A be an intuitionistic multi-anti fuzzy subgroup of a group G and x be any fixed element of
G. Then the following are holds :
(i) x[A](α, β) = [xA](α, β)
(ii) [A](α, β)x = [Ax](α, β) ,∀α, β∈[0,1]k
with αi + βi ≤ 1, ∀i.
Proof For proof (i),
Now [xA](α, β) = { g∈G : µxA(g) ≤ α and νxA(g) ≥ β } with αi + βi ≤ 1, ∀i.
Also x[A](α, β) = x{ y∈G : µA(y) ≤ α and νA(y) ≥ β }
= { xy∈G : µA(y) ≤ α and νA(y) ≥ β } ………………(1)
put xy = g ⇒ y = x-1
g . Then (1) becomes as,
x[A](α, β) = { g∈G : µA(x-1
g) ≤ α and νA(x-1
g) ≥ β }
= { g∈G : µxA(g) ≤ α and νxA(g) ≥ β }
= [xA](α, β)
Therefore, x[A](α, β) = [xA](α, β) ,∀α, β∈[0,1]k
with αi + βi ≤ 1, ∀i.
Hence the proof (i).
For proof (ii),
Now [Ax](α, β) = { g∈G : µAx(g) ≤ α and νAx(g) ≥ β } with αi + βi ≤ 1, ∀i.
Also [A](α, β)x = { y∈G : µA(y) ≤ α and νA(y) ≥ β }x
= { yx∈G : µA(y) ≤ α and νA(y) ≥ β } ………………(2)
put yx = g ⇒ y = gx-1
. Then (2) becomes as,
[A](α, β)x = { g∈G : µA(gx-1
) ≤ α and νA(gx-1
) ≥ β }
= { g∈G : µAx(g) ≤ α and νAx(g) ≥ β }
= [Ax](α, β)
Therefore, [A](α, β)x = [Ax](α, β) ,∀α, β∈[0,1]k
with αi + βi ≤ 1, ∀i.
Hence the proof (ii) and hence the Theorem.
4.5 Theorem
Let A be an intuitionistic multi-anti fuzzy subgroup of a group G. Let x,y be any two
elements of G such that α = max{ µA(x), µA(y) } and β = min{ νA(x), νA(y) }. Then the
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47
following are holds :
(i) xA = yA ⇔ x-1
y∈[A](α, β)
(ii) Ax = Ay ⇔ xy-1
∈[A](α, β)
(iii)
Proof For (i), Now xA = yA ⇔ [xA](α, β) = [yA](α, β) ,∀α, β∈[0,1]k
with αi + βi ≤ 1, ∀i.
⇔ x[A](α, β) = y[A](α, β) ,by Theorem 4.4(i).
⇔ x-1
y∈[A](α, β) ,since each (α, β)-lower cut [A](α, β) is a
subgroup of G. Hence the proof (i).
For (ii), Now Ax = Ay ⇔ [Ax](α, β) = [Ay](α, β) ,∀α, β∈[0,1]k
with αi + βi ≤ 1, ∀i.
⇔ [A](α, β)x = [A](α, β)y ,by Theorem 4.4(ii).
⇔ xy-1
∈[A](α, β) ,since each (α, β)-lower cut [A](α, β) is a
subgroup of G. Hence the proof (ii) and hence the Theorem.
5. HOMOMORPHISM OF INTUITIONISTIC MULTI-ANTI FUZZY
SUBGROUPS
In this section we shall prove some theorems on intuitionistic multi-anti fuzzy subgroups of a group with the
help of a homomorphism.
5.1 Proposition
Let f : X → Y be an onto map. If A and B are intuitionistic multi-fuzzy sets having the
dimension k of X and Y respectively, then for each (α, β)-lower cuts [A](α, β) and [B](α, β) , the
following are holds :
(i) f( [A](α, β) ) ⊆ [f(A)](α, β)
(ii) f-1
( [B](α, β) ) = [f-1
(B)](α, β) ,∀α, β∈[0,1]k
with αi + βi ≤ 1, ∀i.
Proof For (i), Let y∈f( [A](α, β) ).
Then there exists an element x∈[A](α, β) such that f(x) = y.
Then we have µA(x) ≤ α and νA(x) ≥ β ,since x∈[A](α, β) .
⇒ µiA(x) ≤ αi and νiA(x) ≥ βi ,∀i.
⇒ min{µiA(x) : x∈f-1
(y)} ≤ αi and max{νiA(x) : x∈f-1
(y) } ≥ βi ,∀i.
⇒ min{µA(x) : x∈f-1
(y)} ≤ α and max{νA(x) : x∈f-1
(y) } ≥ β
⇒ µf(A)(y) ≤ α and νf(A)(y) ≥ β
⇒ y∈[f(A)](α, β)
Therefore, f( [A](α, β) ) ⊆ [f(A)](α, β) ,∀A∈IMFS(X). Hence the proof (i).
For the proof (ii),
Let x∈[f-1
(B)](α, β) ⇔ {x∈X : µf
-1
(B)(x) ≤ α , νf
-1
(B)(x) ≥ β }
⇔ {x∈X : µif
-1
(B)(x) ≤ αi , νif
-1
(B)(x) ≥ βi },∀i.
⇔ {x∈X : µiB(f(x)) ≤ αi , νiB(f(x)) ≥ βi },∀i.
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48
⇔ {x∈X : µB(f(x)) ≤ α , νB(f(x)) ≥ β }
⇔ { x∈X : f(x)∈[B](α, β) }
⇔ { x∈X : x∈f-1
( [B](α, β) ) }
⇔ f-1
( [B](α, β) )
Hence the proof (ii).
5.2 Theorem
Let f : G1 → G2 be an onto homomorphism and if A is an IMAFSG of group G1, then f(A) is
an IMAFSG of group G2.
Proof By Theorem 3.6, it is enough to prove that each (α, β)-lower cuts [f(A)](α, β) is a
subgroup of G2 for all α, β∈[0,1]k
with αi + βi ≤ 1, ∀i.
Let y1, y2∈[f(A)](α, β) . Then µf(A)(y1) ≤ α , νf(A)(y1) ≥ β and µf(A)(y2) ≤ α , νf(A)(y2) ≥ β
⇒ µif(A)(y1) ≤ αi , νif(A)(y1) ≥ βi and µif(A)(y2) ≤ αi , νif(A)(y2) ≥ βi ,∀i. …………..(1)
By the proposition 5.1(i), we have f( [A](α, β) ) ⊆ [f(A)](α, β) ,∀A∈IMFS(G1)
Since f is onto, there exists some x1 and x2 in G1 such that f(x1) = y1 and f(x2) = y2 .
Therefore, (1) becomes as,
µif(A)( f(x1) ) ≤ αi , νif(A)( f(x1) ) ≥ βi and µif(A)( f(x2) ) ≤ αi , νif(A)( f(x2) ) ≥ βi ,∀i.
⇒ µiA(x1) ≤ µif(A)( f(x1) ) ≤ αi , νiA(x1) ≥ νif(A)( f(x1) ) ≥ βi and
µiA(x2) ≤ µif(A)( f(x2) ) ≤ αi , νiA(x2) ≥ νif(A)( f(x2) ) ≥ βi ,∀i.
⇒ µiA(x1) ≤ αi , νiA(x1) ≥ βi and µiA(x2) ≤ αi , νiA(x2) ≥ βi ,∀i.
⇒ µA(x1) ≤ α , νA(x1) ≥ β and µA(x2) ≤ α , νA(x2) ≥ β
⇒ max{µA(x1), µA(x2)} ≤ α and min{νA(x1), νA(x2)} ≥ β
⇒ µA(x1x2
-1
) ≤ max{µA(x1), µA(x2)} ≤ α and νA(x1x2
-1
) ≥ min{νA(x1), νA(x2)} ≥ β ,since
A∈IMAFSG(G1).
⇒ µA(x1x2
-1
) ≤ α and νA(x1x2
-1
) ≥ β
⇒ x1x2
-1
∈[A](α, β)
⇒ f(x1x2
-1
)∈f( [A](α, β) ) ⊆ [f(A)](α, β)
⇒ f(x1)f(x2
-1
)∈[f(A)](α, β)
⇒ f(x1)f(x2)-1
∈[f(A)](α, β)
⇒ y1y2
-1
∈[f(A)](α, β)
⇒ [f(A)](α, β) is a subgroup of G2 , ∀α, β∈[0,1]k
.
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⇒ f(A)∈IMAFSG(G2)
Hence the Theorem.
5.3 Corollary
If f : G1 → G2 be a homomorphism of a group G1 onto a group G2 and { Ai : i∈I } be a family
of IMAFSG’s of group G1, then f(∪Ai) is an IMAFSG of group G2 .
5.4 Theorem
Let f : G1 → G2 be a homomorphism of a group G1 into a group G2. If B is an IMAFSG of G2 ,
then f-1
(B) is also an IMAFSG of G1.
Proof By Theorem 3.6, it is enough to prove that each (α, β)-lower cuts [f-1
(B)](α, β) is a
subgroup of G1,∀α, β∈[0,1]k
with αi + βi ≤ 1, ∀i.
Let x1, x2∈[f-1
(B)](α, β). Then it implies that
µf
-1
(B)(x1) ≤ α , νf
-1
(B)(x1) ≥ β and µf
-1
(B)(x2) ≤ α , νf
-1
(B)(x2) ≥ β.
⇒ µB(f(x1)) ≤ α , νB(f(x1)) ≥ β and µB(f(x2)) ≤ α , νB(f(x2)) ≥ β.
⇒ max{ µB(f(x1)), µB(f(x2)) } ≤ α and min{ νB(f(x1)), νB(f(x2)) } ≥ β.
⇒ µB( f(x1)f(x2)-1
) ≤ max{ µB(f(x1)), µB(f(x2)) } ≤ α and
νB( f(x1)f(x2)-1
) ≥ min{ νB(f(x1)), νB(f(x2)) } ≥ β ,since B∈IMAFSG(G2).
⇒ f(x1)f(x2)-1
∈[B](α, β)
⇒ f(x1x2
-1
)∈[B](α, β) ,since f is a homomorphism.
⇒ x1x2
-1
∈f-1
( [B](α, β) ) = [f-1
(B)](α, β) ,by the proposition 5.1(ii).
⇒ x1x2
-1
∈[f-1
(B)](α, β)
⇒ [f-1
(B)](α, β) is a subgroup of G1
⇒ f-1
(B) is an IMAFSG of G1.
Hence the Theorem.
5.5 Theorem
Let f : G1 → G2 be a surjective homomorphism and if A is an IMAFNSG of group G1, then
f(A) is also an IMAFNSG of group G2 .
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Proof Let g2∈G2 and y∈f(A).
Since f is surjective,
there exists g1∈G1 and x∈A such that f(x) = y and f(g1) = g2 .
Since A is an IMAFNSG of G1,
µA(g1
-1
xg1) = µA(x) and νA(g1
-1
xg1) = νA(x) ,∀x∈A and g1∈G1.
Now consider, µf(A)(g2
-1
yg2) = µf(A)( f(g1
-1
xg1) ) ,since f is a homomorphism.
= µf(A)(y′
) ,where y′
= f(g1
-1
xg1) = g2
-1
yg2
= min{ µA(x′
) : f(x′
) = y′
for x′∈G1 }
= min{ µA(x′
) : f(x′
) = f(g1
-1
xg1) for x′∈G1 }
= min{ µA(g1
-1
xg1) : f(g1
-1
xg1)=y′
= g2
-1
yg2 for x∈A, g1∈G1}
= min{ µA(x) : f(g1
-1
xg1) = g2
-1
yg2 for x∈A, g1∈G1}
= min{ µA(x) : f(g1)-1
f(x)f(g1) = g2
-1
yg2 for x∈A, g1∈G1}
= min{ µA(x) : g2
-1
f(x)g2 = g2
-1
yg2 for x∈G1}
= min{ µA(x) : f(x) = y for x∈G1}
= µf(A)(y)
Similarly, we can easily prove that νf(A)(g2
-1
yg2) = νf(A)(y) .
Hence f(A) is an IMAFNSG of G2 and hence the Theorem.
5.6 Theorem
If A is an IMAFNSG of a group G, then there exists a natural homomorphism f : G → G/A is
defined by f(x) = xA , ∀x∈G.
Proof Let f : G → G/A be defined by f(x) = xA , ∀x∈G.
Claim1: f is a homomorphism
That is, to prove: f(xy) = f(x)f(y) ,∀x,y∈G.
That is, to prove: (xy)A = (xA)(yA) ,∀x,y∈G.
Since A is an IMAFNSG of G, we have µA(g-1
xg) = µA(x) and
νA(g-1
xg) = νA(x) ,∀x∈A and g∈G.
Or, equivalently, µA(xy) = µA(yx) and νA(xy) = νA(yx) ,∀x,y∈G.
Also, ∀g∈G, we have
(xA)(g) = ( µxA(g), νxA(g) ) = ( µA(x-1
g), νA(x-1
g) )
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(yA)(g) = ( µyA(g), νyA(g) ) = ( µA(y-1
g), νA(y-1
g) )
[(xy)A](g) = ( µ(xy)A(g), ν(xy)A(g) ) = ( µA[(xy)-1
g], νA[(xy)-1
g] )
∀g∈G, by definition 2.16, we have
[(xA)(yA)](g) = ( max[min{µxA(r), µyA(s)} : g = rs ], min[max{νxA(r), νyA(s)} : g = rs ] )
= ( max[min{µA(x-1
r), µA(y-1
s)} : g = rs], min[max{νA(x-1
r), νA(y-1
s)} : g = rs ]
)
Claim2: µA[(xy)-1
g] = max[ min{µA(x-1
r), µA(y-1
s)} : g = rs ] and
νA[(xy)-1
g] = min[ max{νA(x-1
r), νA(y-1
s)} : g = rs ], ∀g∈G.
Now consider µA[(xy)-1
g] = µA[y-1
x-1
g]
= µA[y-1
x-1
rs] ,since g = rs.
= µA[y-1
(x-1
rsy-1
)y]
= µA[x-1
rsy-1
] ,since A is normal.
≤ max{ µA(x-1
r), µA(sy-1
) } ,since A is IMAFSG of G.
= max{ µA(x-1
r), µA(y-1
s) } , ∀g = rs∈G, since A is normal
Therefore, µA[(xy)-1
g] = min[ max{ µA(x-1
r), µA(y-1
s) } : g = rs ] , ∀g∈G.
= max[ min{ µA(x-1
r), µA(y-1
s) } : g = rs ] , ∀g∈G.
Similarly,we can easily prove νA[(xy)-1
g] = min[ max{ νA(x-1
r), νA(y-1
s) } : g = rs ] , ∀g∈G.
Hence the claim2.
Thus, [(xy)A](g) = [(xA)(yA)](g) ,∀g∈G.
⇒ (xy)A = (xA)(yA)
⇒ f(xy) = f(x)f(y)
⇒ f is a homomorphism
Hence the claim1 and hence the Theorem.
6. CONCLUSION
In the theory of fuzzy sets, the level subsets are vital role for its development. Similarly, the
(α, β)-lower cut of an intuitionistic multi-fuzzy sets are very important role for the
development of the theory of intuitionistic multi-fuzzy sets. In this paper an attempt has been
made to study some algebraic natures of intuitionistic multi-anti fuzzy subgroups and their
properties with the help of their (α, β)–lower cut sets.
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