@inbook {IOPORT.05367634,
    author       = {Niu, Ben and Li, Li},
    title        = {A hybrid particle swarm optimization for feed-forward neural network training.},
    year         = {2008},
    booktitle    = {Advanced intelligent computing theories and applications. With aspects of artificial intelligence. 4th international conference on intelligent computing, ICIC 2008, Shanghai, China, September 15--18, 2008. Proceedings},
    isbn         = {978-3-540-85983-3},
    pages        = {494-501},
    publisher    = {Berlin: Springer},
    doi          = {10.1007/978-3-540-85984-0_59},
    abstract     = {Summary: This paper employs a hybrid particle swarm optimization using optimal foraging theory (PSOOFT) for multilayer feed-forward neural network (MFNN) training. Three benchmark classification problems: Iris, Newthyroid and Glass are conducted to measure the performance of PSOOFT based MFNN. The simulation results are also compared with obtained using back Propagation (BP), genetic algorithm (GA) and standard PSO (SPSO) approaches to demonstrate the effectiveness and efficiency of PSOOFT.},
    identifier   = {05367634},
}