Hybrid particle swarm optimization and group method of data handling for inductive modeling

Sharma, Anuraganand and Onwubolu, Godfrey C. and Dayal, Ashwin and Bhartu, Deepak and Shankar, Amal and Katafono, Kenneth (2008) Hybrid particle swarm optimization and group method of data handling for inductive modeling. [Conference Proceedings]

PDF - Published Version Restricted to Registered users only Download (170kB) | Request a copy

Abstract

This paper proposes a new design methodology which is based on hybrid of particle swarm optimization(PSO) and group method of data handling (GMDH). The PSO and GMDH are two well-known nonlinear methods of mathematical modeling. The proposed method constructs a GMDH network model of a population of promising PSO solutions. The new PSO-GMDH hybrid implementation is then applied to modeling and prediction of practical datasets and its results are compared with the results obtained by GMDH-related algorithms. Results presented show that the proposed algorithm appears to perform reasonably well and hence can be applied to real-life prediction and modeling problems.

Item Type:	Conference Proceedings
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Divisions:	Faculty of Science, Technology and Environment (FSTE) > School of Computing, Information and Mathematical Sciences
Depositing User:	Anuraganand Sharma
Date Deposited:	07 Oct 2013 00:52
Last Modified:	13 Aug 2019 21:42
URI:	https://repository.usp.ac.fj/id/eprint/6910

Actions (login required)

View Item