How to Design Optimization Algorithms by Applying Natural Behavioral Patterns.

Format:

Book

Author/Creator:

Omidvar, Rohollah.

Contributor:

Minaei-Bidgoli, Behrooz.

Language:

English

Subjects (All):

Natural language processing (Computer science).

Algorithms.

Physical Description:

1 online resource (209 pages)

Edition:

1st ed.

Place of Publication:

Singapore : Bentham Science Publishers, 2021.

Summary:

How to Design Optimization Algorithms by Applying Natural Behavioral Patterns is a guide book that introduces readers to optimization algorithms based on natural language processing. Readers will learn about the basic concept of optimization, optimization algorithm fundamentals and the methods employed to formulate natural ideas and behaviors into algorithms. Readers will learn how to create their own algorithm from the information provided in the text. The book is a simple reference for students and programming enthusiasts who are interested in learning about optimization and the process of designing algorithms designed to mimic natural phenomena. The information will also benefit engineers who are learning about optimization techniques.

Contents:

Intro

CONTENTS

Cover

Title

Copyright

End User License Agreement

Contents

Foreword

Preface

Dedication

Introduction to Optimization

Nature and Optimization Algorithms

How to Formulate Natural Ideas in Several Algorithms

3.1. SSPCO ALGORITHM (SEE-SEE PARTRIDGE)

3.2. SIMULATION RESULTS

3.3. CHAOTIC SSPCO ALGORITHM

3.4. THE FIRST METHOD: CHAOTIC SSPCO ALGORITHM

3.5. THE SECOND EQUATION: CHAOTIC SSPCO

3.6. SIMULATION AND RESULTS

3.7. DATA CLUSTERING USING BY CHAOTIC SSPCO ALGORITHM

3.8. FITNESS FUNCTION

3.9. EXPERIMENTAL STUDY

3.10. RESULTS AND DISCUSSIONS

3.11. T-TEST

3.12. FRIEDMAN TEST

3.13. A CLUSTERING APPROACH BY SSPCO OPTIMIZATION ALGORITHM BASED ON CHAOTIC INITIAL POPULATION

3.14. FITNESS FUNCTION

3.15. EXPERIMENTAL STUDY

3.16. RESULTS AND DISCUSSIONS

3.17. T-TEST

3.18. TRAVELING SALESMAN PROBLEM

3.19. SIMULATION AND RESULTS

3.20. ESCAPE FROM HUNTER PARTICLE SWARM OPTIMIZATION

3.21. EXPERIMENTAL RESULT

3.22. PROVIDING A BIRD ALGORITHM BASED ON CLASSICAL CONDITIONING LEARNING BEHAVIOUR

3.23. SIMULATION AND RESULTS

How to Transform the Behaviour in Nature into the Algorithm

4.1. CHAOTIC INTIAL POPULATION

4.2. CHAOTIC CREATION OF FOOD SOURCES

Conclusion

References

REFERENCES

Subject Index

Back Cover.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

9789811459597

9811459592

OCLC:

1281961568