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

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Bioinformatics: from nucleotids to networks (N2N)
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.
Keywords
aquaculture, ecology, fuzzy set theory, genetic algorithms, mean square error methods

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Chicago
Fukuda, Shinji, Jun Nakajima, Bernard De Baets, Willem Waegeman, Takahiko Mukai, Ans Mouton, and Norio Orikura. 2011. “A Discussion on the Accuracy-complexity Relationship in Modelling Fish Habitat Preference Using Genetic Takagi-Sugeno Fuzzy Systems.” In Proceedings 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS 2011), 81–86. Piscataway, NJ, USA: IEEE.
APA
Fukuda, S., Nakajima, J., De Baets, B., Waegeman, W., Mukai, T., Mouton, A., & Orikura, N. (2011). A discussion on the accuracy-complexity relationship in modelling fish habitat preference using genetic Takagi-Sugeno fuzzy systems. Proceedings 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS 2011) (pp. 81–86). Presented at the 2011 IEEE 5th International workshop on Genetic and Evolutionary Fuzzy Systems (GEFS 2011), Piscataway, NJ, USA: IEEE.
Vancouver
1.
Fukuda S, Nakajima J, De Baets B, Waegeman W, Mukai T, Mouton A, et al. A discussion on the accuracy-complexity relationship in modelling fish habitat preference using genetic Takagi-Sugeno fuzzy systems. Proceedings 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS 2011). Piscataway, NJ, USA: IEEE; 2011. p. 81–6.
MLA
Fukuda, Shinji, Jun Nakajima, Bernard De Baets, et al. “A Discussion on the Accuracy-complexity Relationship in Modelling Fish Habitat Preference Using Genetic Takagi-Sugeno Fuzzy Systems.” Proceedings 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS 2011). Piscataway, NJ, USA: IEEE, 2011. 81–86. Print.
@inproceedings{2037414,
  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.},
  author       = {Fukuda, Shinji and Nakajima, Jun and De Baets, Bernard and Waegeman, Willem and Mukai, Takahiko and Mouton, Ans and Orikura, Norio},
  booktitle    = {Proceedings 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS 2011)},
  isbn         = {9781612840482},
  keyword      = {aquaculture,ecology,fuzzy set theory,genetic algorithms,mean square error methods},
  language     = {eng},
  location     = {Paris, France},
  pages        = {81--86},
  publisher    = {IEEE},
  title        = {A discussion on the accuracy-complexity relationship in modelling fish habitat preference using genetic Takagi-Sugeno fuzzy systems},
  url          = {http://dx.doi.org/10.1109/GEFS.2011.5949490},
  year         = {2011},
}

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