Numerical method errors analysis examines the difference between true and approximate values. Absolute error is the difference between true and approximate values, while relative error is the ratio of absolute error to true value. Percentage error is calculated by taking the absolute difference between true and approximate values, dividing by the absolute true value, and multiplying by 100. Examples are provided to demonstrate calculating absolute, relative, and percentage errors.
Artificial Intelligence: Introduction, Typical Applications. State Space Search: Depth Bounded
DFS, Depth First Iterative Deepening. Heuristic Search: Heuristic Functions, Best First Search,
Hill Climbing, Variable Neighborhood Descent, Beam Search, Tabu Search. Optimal Search: A
*
algorithm, Iterative Deepening A*
, Recursive Best First Search, Pruning the CLOSED and OPEN
Lists
Definition of Viewing & Clipping?
Viewing pipeline
Viewing the transformation system
Several types of clipping
Cohen-Sutherland Line Clipping
Application of Clipping
Conclusion
This slide contain description about the line, circle and ellipse drawing algorithm in computer graphics. It also deals with the filled area primitive.
Newton's Backward Interpolation explained with example. History of interpolation along with it's advantages and disadvantages. Applications of interpolation in computer sciences.
Here we focuses on Fixed-Point Iterative Technique for solving nonlinear Equations in Numerical Analysis. It is one of the opened-iterative techniques for finding roots called Fixed-Point of Non-linear Equations.
NUMERICA METHODS 1 final touch summary for test 1musadoto
MY FINAL TOUCH SUMMARY FOR TEST 1
ON 6TH MAY 2018
TOPICS AND MATERIALS COVERED
1. Class lecture notes (Basic concepts, errors and roots of function).
2. Lecture’s examples.
3. Past Years Examples.
4. Past Years examination papers.
5. Tutorial Questions.
6. Reference Books + web.
Artificial Intelligence: Introduction, Typical Applications. State Space Search: Depth Bounded
DFS, Depth First Iterative Deepening. Heuristic Search: Heuristic Functions, Best First Search,
Hill Climbing, Variable Neighborhood Descent, Beam Search, Tabu Search. Optimal Search: A
*
algorithm, Iterative Deepening A*
, Recursive Best First Search, Pruning the CLOSED and OPEN
Lists
Definition of Viewing & Clipping?
Viewing pipeline
Viewing the transformation system
Several types of clipping
Cohen-Sutherland Line Clipping
Application of Clipping
Conclusion
This slide contain description about the line, circle and ellipse drawing algorithm in computer graphics. It also deals with the filled area primitive.
Newton's Backward Interpolation explained with example. History of interpolation along with it's advantages and disadvantages. Applications of interpolation in computer sciences.
Here we focuses on Fixed-Point Iterative Technique for solving nonlinear Equations in Numerical Analysis. It is one of the opened-iterative techniques for finding roots called Fixed-Point of Non-linear Equations.
NUMERICA METHODS 1 final touch summary for test 1musadoto
MY FINAL TOUCH SUMMARY FOR TEST 1
ON 6TH MAY 2018
TOPICS AND MATERIALS COVERED
1. Class lecture notes (Basic concepts, errors and roots of function).
2. Lecture’s examples.
3. Past Years Examples.
4. Past Years examination papers.
5. Tutorial Questions.
6. Reference Books + web.
Numerical differentiation and integrationBektu Dida
Differentiation and Integration is the core of Engineering problem solving, and the process is simplified by discretization and In numerical differentiation and integration we will apply this method on it.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
A Strategic Approach: GenAI in EducationPeter 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.
4. Absolute Error
+ The absolute error of a quantity is the absolute
value of the difference between the true value X
and the approximate value x. It is denoted by
5. An approximate value of ᴫ is 3.1428571 and true
value is 3.1415926.
Find the absolute Error
𝐸𝐴 = 𝑋 − 𝑥 = 3.1415926 − 3.1428571
= − 0 .0 0 1 2 6 4 5
= 0 .0 0 1 2 6 4 5
6. Find the absolute errors of the number 8.6 if both of its
digits are correct.
• If the number X is rounded to N decimal places, then 𝐸𝐴 =
1
2
(10−𝑁
)
7. Evaluate the sum S = 2 + 3 + 5 to 4 significant
digits and find its absolute errors.
8. The relative error of a
quantity is the ratio of it’s
absolute error to it’s true
value. It is denoted by ER
Relative Error
ER =
EA
𝑋
9. Find the absolute, relative and percentage errors of the number 8.6 if both of
its digits are correct.
+Solution:
The given number is X =
8.6
Since both digits are
correct so N = 1
The absolute error is,
EA =
1
2
( 10−1
)
= 0.05
The relative error is,
ER =
EA
𝑋
=
0.05
8.6
= 0.0058
The percentage
error is,
EP = 100 ER
= 100 × 0.0058
= o.58
11. How to Calculate
In order to calculate percentage error in some experiment, one needs to follow
the steps written below:
Step 1: Obtain the true value and approximated value.
Step 2: Find the difference between them and take absolute value, ignore if there is a negative
sign. This is known as error.
Step 3: Find the absolute value of true of exact value as well.
Step 4: Divide the absolute error by absolute true value.
Step 5: Multiply the outcome by 100 to convert it to the percent value and add a "%" sign at the
end
12. Example 1: It was assumed that around 1,00,000 people would reach at a certain hill station in a month
summer. But the exact number of people counted was 88,000. Calculate the percentage error.
Solution: Assumed or approximated value = 100000
true value = 88000
The formula for the percentage error is:
PE =
|𝑡𝑟𝑢𝑒 𝑣𝑎𝑙𝑢𝑒− 𝑎𝑝𝑝𝑟𝑜𝑥𝑖𝑚𝑎𝑡𝑒𝑑 𝑣𝑎𝑙𝑢𝑒|
|𝑡𝑟𝑢𝑒 𝑣𝑎𝑙𝑢𝑒|
x 100
PE =
|88000−100000|
|88000|
x 100
PE =
|22000|
|88000|
x 100
PE= 25%
13. Example 2: The approximated time of a ball to reach at ground when dropped from a 4-
meter height is 3 seconds. But during the experiment, it was found that it took 2.1 seconds.
Solution: Approximated time = 3 sec
true time = 2.1 sec
The formula for the percentage error is given by:
PE =
|𝑡𝑟𝑢𝑒 𝑣𝑎𝑙𝑢𝑒−𝑎𝑝𝑝𝑟𝑜𝑥𝑖𝑚𝑎𝑡𝑒𝑑 𝑣𝑎𝑙𝑢𝑒|
|𝑡𝑟𝑢𝑒 𝑣𝑎𝑙𝑢𝑒|
x 100
PE =
|2.1−3|
|2.1|
x 100
PE =
|0.9|
|2.1|
x 100
PE = 42.86%