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Genetic Algorithms
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The article was published on 2002-01-01 and is currently open access. It has received 17039 citations till now.read more
Citations
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Journal ArticleDOI
Magnetic charged system search: a new meta-heuristic algorithm for optimization
TL;DR: The efficiency of the MCSS is examined by application of this algorithm to well-known mathematical benchmarks and three well-studied engineering design problems and the results are compared to those of the CSS, and the improvements are highlighted.
Journal ArticleDOI
Hash key-based image encryption using crossover operator and chaos
TL;DR: Experimental results and security analysis show that the scheme can achieve good encryption result through only one round encryption process, the key space is large enough to resist against common attacks, so the scheme is reliable to be applied in image encryption and secure communication.
Journal ArticleDOI
Speech Analysis for Diagnosis of Parkinson’s Disease Using Genetic Algorithm and Support Vector Machine
TL;DR: A new algorithm for diagnosing of Parkinson’s disease based on voice analysis is proposed and it can be observed that the best classification accuracy may be achieved using Fhi (Hz), Fho ( Hz), jitter (RAP) and shimmer (APQ5).
Book ChapterDOI
Recognizing Products: A Per-exemplar Multi-label Image Classification Approach
TL;DR: This paper presents an efficient approach for per-exemplar multi-label image classification, which targets the recognition and localization of products in retail store images, and provides a large novel dataset and labeling tools for products image search.
Journal ArticleDOI
Task allocation for maximizing reliability of a distributed system using hybrid particle swarm optimization
TL;DR: The experimental results show that the HPSO is robust against different problem size, task interaction density, and network topology, and the proposed method is also more effective and efficient than a genetic algorithm for the test-cases studied.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Book
Genetic Algorithms + Data Structures = Evolution Programs
TL;DR: GAs and Evolution Programs for Various Discrete Problems, a Hierarchy of Evolution Programs and Heuristics, and Conclusions.
Journal ArticleDOI
An Introduction to Genetic Algorithms.
TL;DR: An Introduction to Genetic Algorithms as discussed by the authors is one of the rare examples of a book in which every single page is worth reading, and the author, Melanie Mitchell, manages to describe in depth many fascinating examples as well as important theoretical issues.
Book
Handbook of Genetic Algorithms
TL;DR: This book sets out to explain what genetic algorithms are and how they can be used to solve real-world problems, and introduces the fundamental genetic algorithm (GA), and shows how the basic technique may be applied to a very simple numerical optimisation problem.
Journal ArticleDOI
An Introduction to Population Genetics Theory
James F. Crow,Motoo Kimura +1 more
TL;DR: An introduction to population genetics theory, An introduction to Population Genetics Theory, Population Genetics theory, Population genetics theory as discussed by the authors, Population genetics, population genetics, and population genetics theories, Population Genetic Theory