@inproceedings{a1116be58a664000b82bcdaa59817c41,
title = "Training feedforward neural networks using multi-phase particle swarm optimization",
abstract = "The multi-phase particle swarm optimization algorithm (MPPSO) is a variant of the particle swarm optimization algorithm. It simultaneously evolves multiple groups of particles that change their search criterion when changing the phases, and also incorporates hill-climbing. This paper examines the applicability of MPPSO in training feedforward neural network.",
author = "B. Al-Kazemi and Mohan, {C. K.}",
note = "Publisher Copyright: {\textcopyright} 2002 Nanyang Technological University.; 9th International Conference on Neural Information Processing, ICONIP 2002 ; Conference date: 18-11-2002 Through 22-11-2002",
year = "2002",
doi = "10.1109/ICONIP.2002.1201969",
language = "English (US)",
series = "ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2615--2619",
editor = "Xin Yao and Kunihiko Fukushima and Soo-Young Lee and Lipo Wang and Rajapakse, {Jagath C.}",
booktitle = "ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing",
}