Optimized Genetic Programming Applications: Emerging Research and Opportunities
Optimized Genetic Programming Applications: Emerging Research and Opportunities

Author: Hrnjica, Bahrudin

Publisher: IGI Global

Published: 2018-07-06

Total Pages: 320

ISBN-13: 1522560068

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Data is more valuable than ever in the twenty-first century, and tremendous amounts of data are being generated every second. With a fast-growing information industry, engineers are required to develop new tools and techniques that increase human capabilities of mining useful knowledge from the vast amounts of data. Optimized Genetic Programming Applications: Emerging Research and Opportunities is an essential reference source that explores the concept of genetic programming and its role in managing engineering problems. It also examines genetic programming as a supervised machine learning technique, focusing on implementation and application. As a resource that details both the theoretical aspects and implementation of genetic programming, this book is a useful source for academicians, biological engineers, computer programmers, scientists, researchers, and upper-level students seeking the latest research on genetic programming.

Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms
Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms

Author: Management Association, Information Resources

Publisher: IGI Global

Published: 2020-12-05

Total Pages: 1534

ISBN-13: 1799880990

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Genetic programming is a new and evolutionary method that has become a novel area of research within artificial intelligence known for automatically generating high-quality solutions to optimization and search problems. This automatic aspect of the algorithms and the mimicking of natural selection and genetics makes genetic programming an intelligent component of problem solving that is highly regarded for its efficiency and vast capabilities. With the ability to be modified and adapted, easily distributed, and effective in large-scale/wide variety of problems, genetic algorithms and programming can be utilized in many diverse industries. This multi-industry uses vary from finance and economics to business and management all the way to healthcare and the sciences. The use of genetic programming and algorithms goes beyond human capabilities, enhancing the business and processes of various essential industries and improving functionality along the way. The Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms covers the implementation, tools and technologies, and impact on society that genetic programming and algorithms have had throughout multiple industries. By taking a multi-industry approach, this book covers the fundamentals of genetic programming through its technological benefits and challenges along with the latest advancements and future outlooks for computer science. This book is ideal for academicians, biological engineers, computer programmers, scientists, researchers, and upper-level students seeking the latest research on genetic programming.

Introduction to Genetic Algorithms
Introduction to Genetic Algorithms

Author: S.N. Sivanandam

Publisher: Springer Science & Business Media

Published: 2007-10-24

Total Pages: 453

ISBN-13: 3540731903

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This book offers a basic introduction to genetic algorithms. It provides a detailed explanation of genetic algorithm concepts and examines numerous genetic algorithm optimization problems. In addition, the book presents implementation of optimization problems using C and C++ as well as simulated solutions for genetic algorithm problems using MATLAB 7.0. It also includes application case studies on genetic algorithms in emerging fields.

Linear Genetic Programming
Linear Genetic Programming

Author: Markus F. Brameier

Publisher: Springer Science & Business Media

Published: 2007-02-25

Total Pages: 323

ISBN-13: 0387310304

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Linear Genetic Programming presents a variant of Genetic Programming that evolves imperative computer programs as linear sequences of instructions, in contrast to the more traditional functional expressions or syntax trees. Typical GP phenomena, such as non-effective code, neutral variations, and code growth are investigated from the perspective of linear GP. This book serves as a reference for researchers; it includes sufficient introductory material for students and newcomers to the field.

Handbook of Genetic Programming Applications
Handbook of Genetic Programming Applications

Author: Amir H. Gandomi

Publisher: Springer

Published: 2015-11-06

Total Pages: 589

ISBN-13: 3319208837

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This contributed volume, written by leading international researchers, reviews the latest developments of genetic programming (GP) and its key applications in solving current real world problems, such as energy conversion and management, financial analysis, engineering modeling and design, and software engineering, to name a few. Inspired by natural evolution, the use of GP has expanded significantly in the last decade in almost every area of science and engineering. Exploring applications in a variety of fields, the information in this volume can help optimize computer programs throughout the sciences. Taking a hands-on approach, this book provides an invaluable reference to practitioners, providing the necessary details required for a successful application of GP and its branches to challenging problems ranging from drought prediction to trading volatility. It also demonstrates the evolution of GP through major developments in GP studies and applications. It is suitable for advanced students who wish to use relevant book chapters as a basis to pursue further research in these areas, as well as experienced practitioners looking to apply GP to new areas. The book also offers valuable supplementary material for design courses and computation in engineering.

Genetic Algorithms and Genetic Programming
Genetic Algorithms and Genetic Programming

Author: Michael Affenzeller

Publisher: CRC Press

Published: 2009-04-09

Total Pages: 395

ISBN-13: 1420011324

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Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications discusses algorithmic developments in the context of genetic algorithms (GAs) and genetic programming (GP). It applies the algorithms to significant combinatorial optimization problems and describes structure identification using HeuristicLab as a platform for al

Genetic Algorithm
Genetic Algorithm

Author: Fouad Sabry

Publisher: One Billion Knowledgeable

Published: 2023-07-01

Total Pages: 121

ISBN-13:

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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.

Automatic Re-engineering of Software Using Genetic Programming
Automatic Re-engineering of Software Using Genetic Programming

Author: Conor Ryan

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 150

ISBN-13: 1461546311

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Automatic Re-engineering of Software Using Genetic Programming describes the application of Genetic Programming to a real world application area - software re-engineering in general and automatic parallelization specifically. Unlike most uses of Genetic Programming, this book evolves sequences of provable transformations rather than actual programs. It demonstrates that the benefits of this approach are twofold: first, the time required for evaluating a population is drastically reduced, and second, the transformations can subsequently be used to prove that the new program is functionally equivalent to the original. Automatic Re-engineering of Software Using Genetic Programming shows that there are applications where it is more practical to use GP to assist with software engineering rather than to entirely replace it. It also demonstrates how the author isolated aspects of a problem that were particularly suited to GP, and used traditional software engineering techniques in those areas for which they were adequate. Automatic Re-engineering of Software Using Genetic Programming is an excellent resource for researchers in this exciting new field.

Evolutionary Computation for Modeling and Optimization
Evolutionary Computation for Modeling and Optimization

Author: Daniel Ashlock

Publisher: Springer Science & Business Media

Published: 2006-04-04

Total Pages: 578

ISBN-13: 0387319093

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Concentrates on developing intuition about evolutionary computation and problem solving skills and tool sets. Lots of applications and test problems, including a biotechnology chapter.

Genetic Programming Theory and Practice
Genetic Programming Theory and Practice

Author: Rick Riolo

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 322

ISBN-13: 1441989838

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Genetic Programming Theory and Practice explores the emerging interaction between theory and practice in the cutting-edge, machine learning method of Genetic Programming (GP). The material contained in this contributed volume was developed from a workshop at the University of Michigan's Center for the Study of Complex Systems where an international group of genetic programming theorists and practitioners met to examine how GP theory informs practice and how GP practice impacts GP theory. The contributions cover the full spectrum of this relationship and are written by leading GP theorists from major universities, as well as active practitioners from leading industries and businesses. Chapters include such topics as John Koza's development of human-competitive electronic circuit designs; David Goldberg's application of "competent GA" methodology to GP; Jason Daida's discovery of a new set of factors underlying the dynamics of GP starting from applied research; and Stephen Freeland's essay on the lessons of biology for GP and the potential impact of GP on evolutionary theory.