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Moghadassi, Abdolreza, Nikkholgh, Mahmood Reza, Hosseini, Sayed Mohsen, Parvizian, Fahime, Hashemi, Seyyed Jelaladdin. (1390). A New Approach To Train Multilayer Perceptron Ann Using Error Back-Propagation And Genetic Algorithms Hybrid: A Case Study Of Pvtx Estimation Of Ch4+Cf4 Gas Mixture. نشریه علمی پژوهشی دانشگاه آزاد اسلامی, 2(3), 177-182.
Abdolreza Moghadassi; Mahmood Reza Nikkholgh; Sayed Mohsen Hosseini; Fahime Parvizian; Seyyed Jelaladdin Hashemi. "A New Approach To Train Multilayer Perceptron Ann Using Error Back-Propagation And Genetic Algorithms Hybrid: A Case Study Of Pvtx Estimation Of Ch4+Cf4 Gas Mixture". نشریه علمی پژوهشی دانشگاه آزاد اسلامی, 2, 3, 1390, 177-182.
Moghadassi, Abdolreza, Nikkholgh, Mahmood Reza, Hosseini, Sayed Mohsen, Parvizian, Fahime, Hashemi, Seyyed Jelaladdin. (1390). 'A New Approach To Train Multilayer Perceptron Ann Using Error Back-Propagation And Genetic Algorithms Hybrid: A Case Study Of Pvtx Estimation Of Ch4+Cf4 Gas Mixture', نشریه علمی پژوهشی دانشگاه آزاد اسلامی, 2(3), pp. 177-182.
Moghadassi, Abdolreza, Nikkholgh, Mahmood Reza, Hosseini, Sayed Mohsen, Parvizian, Fahime, Hashemi, Seyyed Jelaladdin. A New Approach To Train Multilayer Perceptron Ann Using Error Back-Propagation And Genetic Algorithms Hybrid: A Case Study Of Pvtx Estimation Of Ch4+Cf4 Gas Mixture. نشریه علمی پژوهشی دانشگاه آزاد اسلامی, 1390; 2(3): 177-182.

A New Approach To Train Multilayer Perceptron Ann Using Error Back-Propagation And Genetic Algorithms Hybrid: A Case Study Of Pvtx Estimation Of Ch4+Cf4 Gas Mixture

International Journal of Industrial Chemistry
دوره 2، شماره 3، آذر 2011، صفحه 177-182    اصل مقاله (443.19 K)
نوع مقاله: research article
نویسندگان
Abdolreza Moghadassi* 1؛ Mahmood Reza Nikkholgh1؛ Sayed Mohsen Hosseini1؛ Fahime Parvizian1؛ Seyyed Jelaladdin Hashemi2
1Department of Chemical Engineering, Faculty of Engineering, Arak University, Arak, Iran.
2Petroleum University of Technology, Ahvaz, Iran.
چکیده
A new algorithm to train Multilayer Perceptron Artificial Neural Network using the genetic and Error Back-propagation algorithms Hybrid has been devised. The new algorithm solves the local minimum trap as a natural result of the standard numerical optimization based methods and by following the global minimums the ANN training accuracy has been highly improved. There are many algorithms for training a Multilayer Perceptron ANN to estimate the PVTx of CH4+CF4 gas mixture. The new devised algorithm is compared and evaluated against these algorithms and indicates a better accuracy.
کلیدواژه‌ها
ARTIFICIAL NEURAL NETWORK؛ GAS MIXTURE؛ GENETIC ALGORITHM؛ HYBRID؛ PVTS ESTIMATION
آمار
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