Title :
Extended immune programming and opposite-based PSO for evolving flexible beta basis function neural tree
Author :
Bouaziz, Souhir ; Alimi, Adel M. ; Abraham, Ajith
Author_Institution :
Res. Group on Intell. Machines (REGIM), Univ. of Sfax, Sfax, Tunisia
Abstract :
In this paper, a new hybrid learning algorithm based on the global optimization techniques, is introduced to evolve the Flexible Beta Basis Function Neural Tree (FBBFNT). The structure is developed using the Extended Immune Programming (EIP) and the Beta parameters and connected weights are optimized using the Opposite-based Particle Swarm Optimization (OPSO) algorithm. The performance of the proposed method is evaluated for time series prediction area and is compared with those of associated methods.
Keywords :
artificial immune systems; learning (artificial intelligence); neural nets; particle swarm optimisation; time series; Beta parameter optimization; EIP; FBBFNT; connected weight optimization; evolving flexible beta basis function neural tree; extended immune programming; global optimization techniques; hybrid learning algorithm; opposite-based PSO; opposite-based particle swarm optimization algorithm; time series prediction; Algorithm design and analysis; Optimization; Sociology; Testing; Time series analysis; Training; Extended Immune Programming; Flexible Beta Basis Function Neural Tree; Opposite-based Particle Swarm Optimization; Time series prediction;
Conference_Titel :
Cybernetics (CYBCONF), 2013 IEEE International Conference on
Conference_Location :
Lausanne
DOI :
10.1109/CYBConf.2013.6617425
