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13 - Electrical and Electronic Engineering, Metallurgy and Materials

University of Southampton

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Article title

Particle swarm optimization aided orthogonal forward regression for unified data modelling

Type

D - Journal article

DOI

10.1109/TEVC.2009.2035921

Title of journal

IEEE Transactions on Evolutionary Computation

Article number

Volume number

Issue number

First page of article

477

ISSN of journal

1089-778X

Year of publication

2010

URL

http://www.eprints.soton.ac.uk/271507

Number of additional authors

Additional information

Significance of output:

The orthogonal least squares (OLS) algorithm has become a standard nonlinear modelling toolkit finding wide applications in diverse fields of science and engineering. This paper describes a major advance and shows that, by incorporating computational intelligence into the OLS algorithm, even more parsimonious models with better generalisation performance can be obtained, while maintaining the simplicity and efficiency of the original algorithm. This combination of attributes makes the approach appealing to practical data modelling practitioners.

Interdisciplinary

Cross-referral requested

Research group

None

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract