A discussion on the accuracy-complexity relationship in modelling fish habitat preference using genetic Takagi-Sugeno fuzzy systems

Shinji Fukuda, Bernard De Baets, Willem Waegeman, Ans M. Mouton, Jun Nakajima, Takahiko Mukai, Norio Onikura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

The relationship among accuracy, interpretability, and complexity of genetic fuzzy systems (GFSs) is a hot topic and is actively studied in the GFS domain. Because different problems have different views of interpretation, it is quite difficult to evaluate the interpretability of GFSs in general. The present study aims to analyze accuracy-complexity relationship in fish habitat modelling using a genetic Takagi-Sugeno fuzzy model called fuzzy habitat preference model (FHPM). The model complexity was defined by bit lengths of a genetic algorithm (GA) assigned to the consequent part of the model, while fuzzy rules and antecedent parts were kept the same. FHPM was developed on the basis of the mean squared errors between the composite habitat preference and the observed presence-absence of fish. The model accuracy was evaluated using multiple performance measures. As a result, the different model complexities resulted in slightly different habitat preference curves and model accuracies. At some complexities, the model accuracy was found to be slightly improved with increased model complexity. The result suggests that an optimal point exists where the model complexity can take a balance between the accuracy and the complexity of the target models, which depends partly on data characteristics and model formulations of the GFSs.

Original languageEnglish
Title of host publicationIEEE SSCI 2011
Subtitle of host publicationSymposium Series on Computational Intelligence - GEFS 2011: 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems
Pages81-86
Number of pages6
DOIs
Publication statusPublished - 2011
EventSymposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems, GEFS 2011 - Paris, France
Duration: Apr 11 2011Apr 15 2011

Publication series

NameIEEE SSCI 2011: Symposium Series on Computational Intelligence - GEFS 2011: 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems

Other

OtherSymposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems, GEFS 2011
CountryFrance
CityParis
Period4/11/114/15/11

All Science Journal Classification (ASJC) codes

  • Discrete Mathematics and Combinatorics
  • Logic

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