Hitch-hiker's guide to genetic algorithms
العنوان: | Hitch-hiker's guide to genetic algorithms |
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المؤلفون: | M. T. Tham, G. B. Wetherill, M. C. South |
المصدر: | Journal of Applied Statistics. 20:153-175 |
بيانات النشر: | Informa UK Limited, 1993. |
سنة النشر: | 1993 |
مصطلحات موضوعية: | Statistics and Probability, Focus (computing), business.industry, Function optimization, Management science, Control (management), Quality control and genetic algorithms, Machine learning, computer.software_genre, Identification (information), Robustness (computer science), Artificial intelligence, Noise (video), Statistics, Probability and Uncertainty, business, Set (psychology), computer |
الوصف: | Genetic algorithms are a set of algorithms with properties which enable them to efficiently search large solution spaces where conventional statistical methodology is inappropriate. They have been used to find effective control and design strategies in industry, for finding rules relating factors and outcomes in medicine and business, and for solving problems ranging from function optimization to identification of patterns in data. They work using ideas from biology, specifically from population genetics, and are appealing because of their robustness in the presence of noise and their ability to cope with highly non-linear, multimodal and multivariate problems. This paper reviews the current literature on genetic algorithms. It looks at ways of defining genetic algorithms for various problems, and examples are introduced to illustrate their application in different contexts. It summarizes the different aspects which have been, and continue to be, the focus of research, and areas requiring further invetiga... |
تدمد: | 1360-0532 0266-4763 |
URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::c20c2263f48aac09179e6e661c15642c https://doi.org/10.1080/02664769300000013 |
رقم الأكسشن: | edsair.doi...........c20c2263f48aac09179e6e661c15642c |
قاعدة البيانات: | OpenAIRE |
تدمد: | 13600532 02664763 |
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