Separation of Lanthanides/ Lanthanides and Actinides
Fuzzy cognitive mapping .ppt new
1. Engineer 2013 , NITK , Suratkal
Rule Based Fuzzy Cognitive Mapping:
Applications in Education
Guided by : Mr. Abdul Kareem
Mtech, Ph.D
Presented By,
Naveen H
Najashree
Ravi Ghael
Shreyas A S
USN
4SF10EC062
4SF10EC061
4SF10EC079
4SF11EC421
Sahyadri college of engineering and management.
3. ABSTRACT
Fostering conceptual and cognitive change.
Creating metaknowledge and exploring hidden
implications of a learner’s understanding.
‘‘So far as the laws of mathematics refer to
reality, they are not certain. And so far as they
are certain, they do not refer to reality.’’
Fuzzy cognitive mapping, Sahyadri college of engineering and management.
4. INTRODUCTION
Fuzzy
Cognitive Mapping(FCM) is a tool for
formalizing understandings of conceptual
and casual relationships.
FCMs
in educational organization.
FCM
combine the strength of cognitive
maps with fuzzy logic.
Fuzzy cognitive mapping, Sahyadri college of engineering and management.
5. FUZZY LOGIC
Embeds human knowledge into working algorithms.
highly complex systems whose behaviors are not
well understood.
If-Then rules are the examples of structured
knowledge.
Important tool in generic decision making.
Fuzzy cognitive mapping, Sahyadri college of engineering and management.
6. FUZZY SETS
Fuzzy Sets can represent the degree to which a
quality is possessed.
Fuzzy Sets (Simple Fuzzy Variables) have values in
the range of [0,1]
Fuzzy cognitive mapping, Sahyadri college of engineering and management.
7. FUZZY COGNITIVE MAPS
•
Fuzzy logic is a system for representing
uncertainty, or possibility.
EXAMPLES OF FCMS:
Fuzzy cognitive mapping, Sahyadri college of engineering and management.
8. FUZZY LOGIC SYSTEM
Fuzzification: transforming crisp values into
linguistic terms of fuzzy sets.
Inference mechanism: Interprets the values in the
input vector and, based on user-defined rules,
assigns values to the output vector. Usually based
on if-then rules.
De-Fuzzification: conversion of fuzzy output to
crisp
Fuzzy cognitive mapping, Sahyadri college of engineering and management.
9. FUZZY AND CRISP SETS
Fuzzy cognitive mapping, Sahyadri college of engineering and management.
10. CONCEPT MAPPING
Graphical representations of a specified conceptual
domain.
Include some aspect of subjectivity.
Representation of the perceptions and beliefs of a
decision maker
Represent a form of distributed intelligence.
structure activity
save mental work
avoid error.
Fuzzy cognitive mapping, Sahyadri college of engineering and management.
12. FUZZY LINGUISTIC VARIABLES
Fuzzy Linguistic Variables are used to represent
qualities spanning a particular spectrum
Social :{police vigilance, theft } ;
Fuzzy cognitive mapping, Sahyadri college of engineering and management.
14. CLASSIFICATION OF FUZZY INFERENCE
METHODS
Fuzzy cognitive mapping, Sahyadri college of engineering and management.
15. MAMDANI'S METHOD
Step 1: Evaluate the antecedent for each rule.
Step 2: Obtain each rule's conclusion.
Step 3: Aggregate conclusions.
Step 4: Defuzzification.
Fuzzy cognitive mapping, Sahyadri college of engineering and management.
16. CAUSALITY AND FCMS
The relation between causes and effects
Fuzzy logic allows the representation of fuzzy concepts
and degree of causality.
FCMs are a tool for representing a dynamic process
and modeling the process in real-time.
FCMs is the temporal and causal nature.
Fuzzy cognitive mapping, Sahyadri college of engineering and management.
17. ADVANTAGES
1.
FCMs capture more information in the
relationships between concepts.
2. FCMs are dynamic.
3. FCMs express hidden relationships.
4. FCMs are combinable.
5. FCMs are tunable.
Fuzzy cognitive mapping, Sahyadri college of engineering and management.
18. CONCLUSION
Potential usefulness of fuzzy cognitive mapping
in educational organization settings.
Combining the capability of fuzzy logic to represent soft
knowledge domains with dynamic modeling.
Stimulates educational research to recognize the
unique applicability of fuzzy logic to our field.
Fuzzy cognitive mapping, Sahyadri college of engineering and management.
19. REFERENCES
Jason R. Cole, Kay A. Persichitte, Fuzzy Cognitive
Mapping, University of Northern Colorado,
Kosko B. Fuzzy cognitive maps. Int J Man-Mach
Stud 1986;24:65]75.
Gardner H. The unschooled mind: How children
learn and how schools should teach.
João Paulo Carvalho José A. B. Tomé Rule Based
Fuzzy Cognitive Maps and Fuzzy Cognitive Maps –
A Comparative StudyINESC - Instituto de
Engenharia de Sistemas e Computadores