A PARALLEL GENETIC/NEURAL NETWORK LEARNING ALGORITHM FOR MIMD SHARED-MEMORY MACHINES

doi:10.1109/72.329686

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DC Field	Value	Language
dc.contributor.author	HUNG, SL	en_US
dc.contributor.author	ADELI, H	en_US
dc.date.accessioned	2014-12-08T15:03:43Z	-
dc.date.available	2014-12-08T15:03:43Z	-
dc.date.issued	1994-11-01	en_US
dc.identifier.issn	1045-9227	en_US
dc.identifier.uri	http://dx.doi.org/10.1109/72.329686	en_US
dc.identifier.uri	http://hdl.handle.net/11536/2251	-
dc.description.abstract	A new algorithm is presented for training of multilayer feedforward neural networks by integrating a genetic algorithm with an adaptive conjugate gradient neural network learning algorithm. The parallel hybrid learning algorithm has been implemented in C on an MIMD shared memory machine (Cray Y-MP8/864 supercomputer). It has been applied to two different domains, engineering design and image recognition. The performance of the algorithm has been evaluated by applying it to three examples. The superior convergence property of the parallel hybrid neural network learning algorithm presented in this paper is demonstrated.	en_US
dc.language.iso	en_US	en_US
dc.title	A PARALLEL GENETIC/NEURAL NETWORK LEARNING ALGORITHM FOR MIMD SHARED-MEMORY MACHINES	en_US
dc.type	Article	en_US
dc.identifier.doi	10.1109/72.329686	en_US
dc.identifier.journal	IEEE TRANSACTIONS ON NEURAL NETWORKS	en_US
dc.citation.volume	5	en_US
dc.citation.issue	6	en_US
dc.citation.spage	900	en_US
dc.citation.epage	909	en_US
dc.contributor.department	土木工程學系	zh_TW
dc.contributor.department	Department of Civil Engineering	en_US
dc.identifier.wosnumber	WOS:A1994PQ76300004	-
dc.citation.woscount	78	-
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