McInerney M. and Dhawan A. P., Use of genetic algorithms with backpropagation in training of feedforward neural networks, Proc. IEEE lnt. Conf. on Neural Networks, IEEE-ICNN'93 , 203-208, 1993  Home/Search   Document Not in Database   Summary   Related Articles   Check

....In [40] the modeling of the German stock index DAX is attempted with a neuro fuzzy approach. 2. 2 Neural networks and Evolutionary algorithms Fundamental implementations of neural networks generated and tuned by genetic algorithms can be found in a series of publications [41] 42] 43] 44] [45], 46] The idea behind the implementation of such a hybrid system is the adoption of an evolutionary algorithm for the determination of neural network s weights or the neural network s architecture, or both. In the first case, neural networks are tuned by evolutionary algorithm, rather than ....

McInerney M. and Dhawan A. P., Use of genetic algorithms with backpropagation in training of feedforward neural networks, Proc. IEEE lnt. Conf. on Neural Networks, IEEE-ICNN'93 , 203-208, 1993

....this problem. One is to use Genetic Algorithms (GA) which search a large parameter space. However, this means longer training time. GA has been used in experiments for improving BP in several ways: ffl Avoid local minima by adjusting the weights by GA, either initially [32] or during training [33]. ffl Adjust learning rate and momentum term during training [33] ffl Find the optimal neuron interconnections by adding and deleting connections between neurons in the same and different layers [34] Since the topic of initial parameters is covered in many papers, it is not included in this ....

....a large parameter space. However, this means longer training time. GA has been used in experiments for improving BP in several ways: ffl Avoid local minima by adjusting the weights by GA, either initially [32] or during training [33] ffl Adjust learning rate and momentum term during training [33]. ffl Find the optimal neuron interconnections by adding and deleting connections between neurons in the same and different layers [34] Since the topic of initial parameters is covered in many papers, it is not included in this work. Still, the learning parameters are very important for the ....

Michael McInerney and Atam P. Dhawan, "Use of genetic algorithms with back propagation in training of feed-forward neural networks," Proc. of IEEE Int. Conference on Neural Networks, pp. 203--208, 1993.

....Deer, Barry C. 660] deFigueiredo, Rui J. P. 918] Degener, T. F. 245] Dekker, Laura, 189] Delgado, A. 329] Denaro, D. 327] Dengiz, Berna, 164] Deo, Brahma, 28] Deodhar, D. 779] de Ovidio, F. 578] Der, R. 390] DeRouin, E. 773] Destri, G. 330] Dhawan, Atam P. [805, 867, 868] Dhawan, Atam, 62] Diessel, O. F. 869] Dill, Franz A. 660] Di Stefano, G. 29] Distefano, G. 592] Dobbins, R. W. 661] Dobnikar, Andrej, 30, 165, 246, 662] Dodd, Nigel, 663, 664, 806] Dolan, Charles P. 642] Dominic, Stephen, 132, 955, 956, 959] Dorado, Julian, 377] ....

....344, 393] May, Gary S. 459, 469, 546] Mayer, Helmut A. 180, 369, 549] McCaskill, J. S. 821] McCullagh, J. 482, 624] McDonnell, John R. 61, 117, 822, 823, 824, 825, 826, 827, 828] McGregor, Douglas R. 829, 830, 831, 832, 833] McInerney, John, 614, 615, 616] McInerney, Michael, [805] McInerney, M. 62] Mecklenburg, Klaus, 910] Meeden, Lisa A. 455] Meisel, J. 417] Melsheimer, S. S. 55] Menczer, Filippo, 834, 835, 836] Mendoca, P. R. S. 480] Mendonca, P. R. S. 317] Meng, Qing chun, 277] Merelo, J. J. 153, 198, 293, 513, 865, 866] Meservy, R. D. 346] ....

[Article contains additional citation context not shown here]

Michael McInerney and Atam P. Dhawan. Use of genetic algorithms with back propagation in training of feed-forward neural networks. In IEEENN93 [768], pages 203--208. ga:MMcInerney93a.

....[204, 205] Davis, Lawrence, 206, 207, 208, 209, 210] Davis, Thomas Elder, 973] Deb, Kalyanmoy, 217, 375, 376, 378, 381] Deboeck, Guido, 218, 219] deFigueiredo, Rui J. P. 944] Delaney, B. 239] Denham, M. J. 797] Deodhar, D. 538] Deugo, Dwight, 220, 221] Dhawan, Atam P. [222, 223, 657, 806] Dike, B. A. 834, 837] Dissanayake, M. W. M. G. 1072] Diver, D. A. 224] Dix, T. I. 815] Dobnikar, Andrej, 225] Dockx, K. 226] Doi, Hirofumi, 1045] Dorey, Robert E. 667, 668] Dorigo, Marco, 9, 227, 228, 229, 230, 231, 232, 233] Dosi, G. 682] Duan, Q. Y. 234] Dubois, ....

....Mazumder, Pinaki, 695] McCleod, M. D. 696] McCormack, C. J. 839] McCormack, Christopher J. 697] McCullagh, J. 123] McDonnell, John R. 698, 699, 700, 701, 702, 703] McGarrah, D. B. 524] McGraw, G. 637] McGregor, Douglas R. 704, 705, 706, 707, 708, 709] McInerney, Michael, [657] Medsker, C. 710] Mellish, C. 270] Mendes, E. M. 287, 305] Meng, Qing chun, 426, 711] Menozzi, J. J. 839] Menozzi, John J. 697] Menth, Stefan, 67] Merelo, J. J. 802, 803] Merkle, Laurence D. 712] Merz, Jr. K. M. 619] Meyer, Claudia M. 806] Meyer, Robert R. 843, ....

[Article contains additional citation context not shown here]

Michael McInerney and Atam P. Dhawan. Use of genetic algorithms with back propagation in training of feed-forward neural networks. In IEEENN93 [486], pages 203--208. ga:MMcInerney93a.

.... McInerney and Dhawan improved Kitano s algorithm by using the GA to escape from the local minima found by the backpropagation during the training of the NNs (rather than initializing the NNs using the GAs and then tuning it using BP) They also provided a dynamic adaptation of the NN learning rate (McInerney and Dhawan, 1993). For an extensive review of the use of GAs in NNs, the reader is encouraged to consult references (Schaffer et al. 1992) and (Yao, 1992) 15.5 FL Controller Tuned by NNs Among the first to propose the combined use of FL and NNs was S.C. Lee (Lee and Lee, 1974) who in 1974 proposed a ....

M. McInerney and A.P. Dhawan. Use of Genetic Algorithms with Backpropagation in Training of Feedforward Neural Networks. In 1993 IEEE International Conference on Neural Networks, pages 203--208, San Francisco, CA., March 1993.

No context found.

: Michael McInerney and Atam P. Dhawan: "Use of Genetic Algorithms with Back-Propagation in Training of Feed-Forward Neural Networks", in: International Conference of Neural Networks, Vol. I, pp 203-208, San Francisco, IEEE.

No context found.

: Michael McInerney and Atam P. Dhawan: "Use of Genetic Algorithms with Back-Propagation in Training of Feed-Forward Neural Networks", in: International Conference of Neural Networks, Vol. I, pp 203-208, San Francisco, IEEE.

No context found.

Michael McInerney and Atam P. Dhawan. Use of Genetic Algorithms with Back Propagation in Training of Feed-Forward Neural Networks. preprint from the Author; don't "no" about publication.

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC