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Mohnyin University
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Myanmar Institute of Information Technology
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National Management Degree College
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Naypyitaw State Academy
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Pathein University
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Sagaing University of Education
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Taunggyi University
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Technological University, Hmawbi
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Technological University (Kyaukse)
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University of Computer Studies, Mandalay
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University of Computer Studies, Meikhtila
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University of Computer Studies Pathein
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University of Computer Studies, Taungoo
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University of Computer Studies, Yangon
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University of Dental Medicine Mandalay
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University of Dental Medicine, Yangon
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University of Information Technology
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University of Mandalay
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Yangon University of Education
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Yezin Agricultural University
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New Index
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Item
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Decision Making Process of Genetic Algorithm Based Fuzzy Rules Optimization [Excavation Step in Construction Workface]
http://hdl.handle.net/20.500.12678/0000003349
http://hdl.handle.net/20.500.12678/000000334931b9ca8b-7a14-488e-9501-0402fd2daade
35d242e3-dec5-44bf-a09c-3b6f88ae3a08
Name / File | License | Actions |
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Publication type | ||||||
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Article | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | Decision Making Process of Genetic Algorithm Based Fuzzy Rules Optimization [Excavation Step in Construction Workface] | |||||
Language | en | |||||
Publication date | 2010-12-16 | |||||
Authors | ||||||
Kyaw, Phyo Ma Ma | ||||||
Myaing, Khin Lay | ||||||
Description | ||||||
Combination of Fuzzy logic and GeneticAlgorithm is used for searching of optimal solutions.To obtain the globally optimal rules, the Fuzzy rulebasesare searched by means of Genetic Algorithm.In Fuzzy inference mechanism, GA is used to find theoptimal rules. Defuzzified the rules from inferenceand then the optimal result is produced. This paperintroduced the main concept of Fuzzy Logic, GeneticAlgorithm and the use of GA and Fuzzy Logic. Theinput values entered by user are fuzzified withTriangular or Trapezoidal membership function.These memberships’ values are used to find the activerules. These active rules are optimized by GA withvarious population sizes. Then the optimal rule isdefuzzified with Weight Average Method and then theresults are described as number of workers andworking days. Genetic Algorithms mimic the processof natural selection, creating a number of potentiallyoptimal solutions to some complex search problem.Computer simulations demonstrate that the fuzzylogic system with genetic algorithms processes goodrobustness. | ||||||
Keywords | ||||||
Fuzzy Logic, Genetic Algorithms | ||||||
Identifier | http://onlineresource.ucsy.edu.mm/handle/123456789/1109 | |||||
Journal articles | ||||||
Fifth Local Conference on Parallel and Soft Computing | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |