Genetic Algorithm: Fundamentals and Applications

ยท One Billion Knowledgeable ยท แƒฎแƒ”แƒšแƒแƒ•แƒœแƒฃแƒ แƒ˜ แƒ˜แƒœแƒขแƒ”แƒšแƒ”แƒฅแƒขแƒ˜แƒก แƒ›แƒ˜แƒ”แƒ  แƒ›แƒแƒ—แƒฎแƒ แƒแƒ‘แƒ˜แƒšแƒ˜ Mason-แƒ˜แƒกแƒ’แƒแƒœ (Google-แƒ˜แƒ“แƒแƒœ)
แƒแƒฃแƒ“แƒ˜แƒแƒฌแƒ˜แƒ’แƒœแƒ˜
2 แƒกแƒ—, 38 แƒฌแƒ—
แƒจแƒ”แƒฃแƒ›แƒแƒ™แƒšแƒ”แƒ‘แƒ”แƒšแƒ˜
แƒ›แƒ˜แƒกแƒแƒฆแƒ”แƒ‘แƒ˜
แƒฎแƒ”แƒšแƒแƒ•แƒœแƒฃแƒ แƒ˜ แƒ˜แƒœแƒขแƒ”แƒšแƒ”แƒฅแƒขแƒ˜แƒก แƒ›แƒ˜แƒ”แƒ  แƒ›แƒแƒ—แƒฎแƒ แƒแƒ‘แƒ˜แƒšแƒ˜
แƒ แƒ”แƒ˜แƒขแƒ˜แƒœแƒ’แƒ”แƒ‘แƒ˜ แƒ“แƒ แƒ›แƒ˜แƒ›แƒแƒฎแƒ˜แƒšแƒ•แƒ”แƒ‘แƒ˜ แƒ“แƒแƒฃแƒ“แƒแƒกแƒขแƒฃแƒ แƒ”แƒ‘แƒ”แƒšแƒ˜แƒ ย แƒจแƒ”แƒ˜แƒขแƒงแƒ•แƒ”แƒ— แƒ›แƒ”แƒขแƒ˜
แƒ’แƒกแƒฃแƒ แƒ— 15 แƒฌแƒ—-แƒ˜แƒแƒœแƒ˜ แƒœแƒ˜แƒ›แƒฃแƒจแƒ˜? แƒ›แƒแƒฃแƒกแƒ›แƒ˜แƒœแƒ”แƒ— แƒ›แƒแƒก แƒœแƒ”แƒ‘แƒ˜แƒกแƒ›แƒ˜แƒ”แƒ  แƒ“แƒ แƒแƒก, แƒฎแƒแƒ–แƒ’แƒแƒ แƒ”แƒจแƒ” แƒ แƒ”แƒŸแƒ˜แƒ›แƒจแƒ˜แƒช แƒ™แƒ˜.ย 
แƒ“แƒแƒ›แƒแƒขแƒ”แƒ‘แƒ

แƒแƒ› แƒแƒฃแƒ“แƒ˜แƒแƒฌแƒ˜แƒ’แƒœแƒ˜แƒก แƒจแƒ”แƒกแƒแƒฎแƒ”แƒ‘

What Is Genetic Algorithm


In the fields of computer science and operations research, a genetic algorithm (GA) is a metaheuristic that is modeled after the process of natural selection and is a subcategory of evolutionary algorithms (EA), which are a broader category. By relying on biologically inspired operators like mutation, crossover, and selection, genetic algorithms are often employed to develop high-quality solutions to optimization and search problems. This is accomplished through the use of genetic programming. Applications of GA include, but are not limited to, improving the efficiency of decision trees through optimization, deciphering sudoku puzzles, optimizing hyperparameters, drawing causal inferences, and other similar tasks.


How You Will Benefit


(I) Insights, and validations about the following topics:


Chapter 1: Genetic algorithm


Chapter 2: Genetic programming


Chapter 3: Particle filter


Chapter 4: Schema (genetic algorithms)


Chapter 5: Universal Darwinism


Chapter 6: Metaheuristic


Chapter 7: Learning classifier system


Chapter 8: Rule-based machine learning


Chapter 9: Genetic representation


Chapter 10: Fitness function


(II) Answering the public top questions about genetic algorithm.


(III) Real world examples for the usage of genetic algorithm in many fields.


(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of genetic algorithm' technologies.


Who This Book Is For


Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of genetic algorithm.

แƒแƒ•แƒขแƒแƒ แƒ˜แƒก แƒจแƒ”แƒกแƒแƒฎแƒ”แƒ‘

Fouad Sabry is the former Regional Head of Business Development for Applications at HP in Southern Europe, Middle East, and Africa (SEMEA). Fouad has received his B.Sc. of Computer Systems and Automatic Control in 1996, dual masterรขย€ย™s degrees from University of Melbourne (UoM) in Australia, Master of Business Administration (MBA) in 2008, and Master of Management in Information Technology (MMIT) in 2010.ย 

Fouad has more than 20 years of experience in Information Technology and Telecommunications fields, working in local, regional, and international companies, such as Vodafone and IBM in Middle East and Africa (MEA) region. Fouad joined HP Middle East (ME), based in Dubai, United Arab Emirates (UAE) in 2013 and helped develop the software business in tens of markets across Southern Europe, Middle East, and Africa (SEMEA) regions. Currently, Fouad is an entrepreneur, author, futurist, focused on Emerging Technologies, and Industry Solutions, and founder of One Billion Knowledgeable (1BK) Initiative.

แƒแƒ› แƒแƒฃแƒ“แƒ˜แƒแƒฌแƒ˜แƒ’แƒœแƒ˜แƒก แƒจแƒ”แƒคแƒแƒกแƒ”แƒ‘แƒ

แƒ’แƒ•แƒ˜แƒ—แƒฎแƒแƒ แƒ˜แƒ— แƒ—แƒฅแƒ•แƒ”แƒœแƒ˜ แƒแƒ–แƒ แƒ˜.

แƒ˜แƒœแƒคแƒแƒ แƒ›แƒแƒชแƒ˜แƒ แƒ›แƒแƒกแƒ›แƒ”แƒœแƒ˜แƒก แƒจแƒ”แƒกแƒแƒฎแƒ”แƒ‘

แƒกแƒ›แƒแƒ แƒขแƒคแƒแƒœแƒ”แƒ‘แƒ˜ แƒ“แƒ แƒขแƒแƒ‘แƒšแƒ”แƒขแƒ”แƒ‘แƒ˜
แƒ“แƒแƒแƒ˜แƒœแƒกแƒขแƒแƒšแƒ˜แƒ แƒ”แƒ— Google Play Books แƒแƒžแƒ˜ Android แƒ“แƒ iPad/iPhone แƒ›แƒแƒฌแƒงแƒแƒ‘แƒ˜แƒšแƒแƒ‘แƒ”แƒ‘แƒ˜แƒกแƒ—แƒ•แƒ˜แƒก. แƒ˜แƒก แƒแƒ•แƒขแƒแƒ›แƒแƒขแƒฃแƒ แƒแƒ“ แƒ’แƒแƒœแƒแƒฎแƒแƒ แƒชแƒ˜แƒ”แƒšแƒ”แƒ‘แƒก แƒกแƒ˜แƒœแƒฅแƒ แƒแƒœแƒ˜แƒ–แƒแƒชแƒ˜แƒแƒก แƒ—แƒฅแƒ•แƒ”แƒœแƒก แƒแƒœแƒ’แƒแƒ แƒ˜แƒจแƒ—แƒแƒœ แƒ“แƒ แƒกแƒแƒจแƒฃแƒแƒšแƒ”แƒ‘แƒแƒก แƒ›แƒแƒ’แƒชแƒ”แƒ›แƒ—, แƒฌแƒแƒ˜แƒ™แƒ˜แƒ—แƒฎแƒแƒ— แƒกแƒแƒกแƒฃแƒ แƒ•แƒ”แƒšแƒ˜ แƒ™แƒแƒœแƒขแƒ”แƒœแƒขแƒ˜ แƒœแƒ”แƒ‘แƒ˜แƒกแƒ›แƒ˜แƒ”แƒ  แƒแƒ“แƒ’แƒ˜แƒšแƒแƒก, แƒ แƒแƒ’แƒแƒ แƒช แƒแƒœแƒšแƒแƒ˜แƒœ, แƒ˜แƒกแƒ” แƒฎแƒแƒ–แƒ’แƒแƒ แƒ”แƒจแƒ” แƒ แƒ”แƒŸแƒ˜แƒ›แƒจแƒ˜.
แƒšแƒ”แƒžแƒขแƒแƒžแƒ”แƒ‘แƒ˜ แƒ“แƒ แƒ™แƒแƒ›แƒžแƒ˜แƒฃแƒขแƒ”แƒ แƒ”แƒ‘แƒ˜
แƒจแƒ”แƒ’แƒ˜แƒซแƒšแƒ˜แƒแƒ— แƒฌแƒแƒ˜แƒ™แƒ˜แƒ—แƒฎแƒแƒ— Google Play-แƒ–แƒ” แƒจแƒ”แƒซแƒ”แƒœแƒ˜แƒšแƒ˜ แƒฌแƒ˜แƒ’แƒœแƒ”แƒ‘แƒ˜ แƒ—แƒฅแƒ•แƒ”แƒœแƒ˜ แƒ™แƒแƒ›แƒžแƒ˜แƒฃแƒขแƒ”แƒ แƒ˜แƒก แƒ•แƒ”แƒ‘ แƒ‘แƒ แƒแƒฃแƒ–แƒ”แƒ แƒ˜แƒก แƒ’แƒแƒ›แƒแƒงแƒ”แƒœแƒ”แƒ‘แƒ˜แƒ—.

แƒ›แƒ”แƒขแƒ˜ แƒแƒ•แƒขแƒแƒ แƒ˜แƒกแƒ’แƒแƒœ Fouad Sabry

แƒ›แƒกแƒ’แƒแƒ•แƒกแƒ˜ แƒแƒฃแƒ“แƒ˜แƒแƒฌแƒ˜แƒ’แƒœแƒ”แƒ‘แƒ˜

แƒ›แƒ—แƒฎแƒ แƒแƒ‘แƒ”แƒšแƒ˜ Mason-แƒ˜แƒก แƒ›แƒ˜แƒ”แƒ