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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
A Data-Mining Approach to Monitoring Wind Turbines
Andrew Kusiak,Anoop Verma +1 more
TL;DR: In this article, data-mining algorithms are employed to construct prediction models for wind turbine faults and a three-stage prediction process is followed: prediction of a fault of any kind, prediction of specific faults of the system, and identification on unseen faults.
Proceedings ArticleDOI
Evolutionary algorithms for multi-objective optimization: performance assessments and comparisons
TL;DR: This paper aims to analyze the strength and weakness of different evolutionary methods proposed in the literature for multi-objective MO optimization, and proposes a few useful performance measures for better and comprehensive examination of each approach both quantitatively and qualitatively.
Journal ArticleDOI
Optimization of multipass turning operations with genetic algorithms
G. C. Onwubolu,T. Kumalo +1 more
TL;DR: In this article, a new optimization technique based on genetic algorithms for the determination of the cutting parameters in multipass machining operations is proposed, which can be integrated into an intelligent manufacturing system for solving complex machining optimization problems.
Journal ArticleDOI
Code aperture optimization for spectrally agile compressive imaging
Henry Arguello,Gonzalo R. Arce +1 more
TL;DR: The concept of CASSI is extended to a system admitting multiple shot measurements, which leads not only to higher quality of reconstruction but also to spectrally selective imaging when the sequence of code aperture patterns is optimized.
Journal ArticleDOI
Interconnect-Based Design Methodologies for Three-Dimensional Integrated Circuits
TL;DR: 3-D NoC topologies incorporating dissimilar 3-D interconnect structures are reviewed as a promising solution for communication limited systems-on-chip (SoC).
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