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Parallel Differential Evolution Algorithm with Multiple Trial Vectors to Artificial Neural Network Training
http://hdl.handle.net/20.500.12678/0000004767
http://hdl.handle.net/20.500.12678/0000004767dd60cb74-2ff4-4993-a209-3fde89ef24a2
c254ff7c-6850-409d-b4b7-6cb201782014
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Article | ||||||
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Title | ||||||
Title | Parallel Differential Evolution Algorithm with Multiple Trial Vectors to Artificial Neural Network Training | |||||
Language | en | |||||
Publication date | 2015-02-05 | |||||
Authors | ||||||
Thein, Htet Thazin Tike | ||||||
Tun, Khin Mo Mo | ||||||
Description | ||||||
In this paper, parallel differential evolutionalgorithm with multiple trial vectors for trainingartificial neural networks (ANNs) is presented. Theproposed method is PDEA, which is a DE-ANN+modified by adding island model. Within PDEA, anisland model is designed to cooperatively search forthe global optima in search space. By combining thestrengths of the differential evolution algorithm withmultiple trial vectors and island model, PDEA greatlyimproves the optimization performance. PDEAalgorithm is used for ANN training to classify theparity-p problem. Results obtained using proposedalgorithm has been compared to the results obtainedusing other evolutionary algorithms. | ||||||
Keywords | ||||||
Artificial Intelligence, artificial neural network, differential evolution algorithm, multiple and trial vectors, training method, island model | ||||||
Identifier | http://onlineresource.ucsy.edu.mm/handle/123456789/63 | |||||
Journal articles | ||||||
Thirteenth International Conferences on Computer Applications(ICCA 2015) | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |