caa a22 4500 606160035 CHVBK 20210128100627.0 cr unu---uuuuu 210128e20151101xx s 000 0 eng 10.1007/s00521-015-1847-6 doi (NATIONALLICENCE)springer-10.1007/s00521-015-1847-6 Designing evolutionary feedforward neural networks using social spider optimization algorithm [Elektronische Daten] [Seyedeh Mirjalili, Shahrzad Saremi, Seyed Mirjalili] Training feedforward neural networks (FNNs) is considered as a challenging task due to the nonlinear nature of this problem and the presence of large number of local solutions. The literature shows that heuristic optimization algorithms are able to tackle these problems much better than the mathematical and deterministic methods. In this paper, we propose a new trainer using the recently proposed heuristic algorithm called social spider optimization (SSO) algorithm. The trained FNN by SSO (FNNSSO) is benchmarked on five standard classification data sets: XOR, balloon, Iris, breast cancer, and heart. The results are verified by the comparison with five other well-known heuristics. The results prove that the proposed FNNSSO is able to provide very promising results compared with other algorithms. The Natural Computing Applications Forum, 2015 Optimization nationallicence Training neural network nationallicence Social spider optimization nationallicence Feedforward neural networks nationallicence Learning nationallicence Mirjalili Seyedeh Zharfa Pajohesh System (ZPS) Co., Unit 5, NO. 30, West 208 St., Third Sq. Tehranpars, P. O. Box: 1653745696, Tehran, Iran aut Saremi Shahrzad School of Information and Communication Technology, Griffith University, Nathan Campus, 4111, Brisbane, QLD, Australia aut Mirjalili Seyed Zharfa Pajohesh System (ZPS) Co., Unit 5, NO. 30, West 208 St., Third Sq. Tehranpars, P. O. Box: 1653745696, Tehran, Iran aut Neural Computing and Applications Springer London 26/8(2015-11-01), 1919-1928 0941-0643 26:8<1919 2015 26 521 https://doi.org/10.1007/s00521-015-1847-6 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-015-1847-6 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Mirjalili Seyedeh Zharfa Pajohesh System (ZPS) Co., Unit 5, NO. 30, West 208 St., Third Sq. Tehranpars, P. O. Box: 1653745696, Tehran, Iran aut NATIONALLICENCE 700 1- Saremi Shahrzad School of Information and Communication Technology, Griffith University, Nathan Campus, 4111, Brisbane, QLD, Australia aut NATIONALLICENCE 700 1- Mirjalili Seyed Zharfa Pajohesh System (ZPS) Co., Unit 5, NO. 30, West 208 St., Third Sq. Tehranpars, P. O. Box: 1653745696, Tehran, Iran aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/8(2015-11-01), 1919-1928 0941-0643 26:8<1919 2015 26 521