抄録
Genetic fuzzy systems have a potential to be applied to ecological studies as a tool for species distribution modelling and habitat evaluation. However, no study has focused on how different model formulations affect habitat preference evaluation and performance of the model. The present study therefore aims to assess the effect of model formulations on habitat preference evaluation through the optimization process. We employed a genetic algorithm (GA)-optimized Takagi-Sugeno fuzzy model for evaluating habitat preference of topmouth gudgeon (Pseudorasbora parva), a freshwater fish in Japan. The model was trained based on the mean square error (MSE) between composite habitat preference and observed presence-absence, and evaluated using confusion matrix-derived performance measures such as kappa and correctly classified instances (CCI). The present results clearly illustrated the effect of model formulations on habitat preference evaluation, which appeared as different trends in habitat preference curves (HPCs) and the variance. The use of the product equation is recommended in view of model accuracy and consistency in HPCs. Further studies would be necessary for better understanding of model behaviour to different conditions of data such as sample size and prevalence.
本文言語 | 英語 |
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ホスト出版物のタイトル | Proceedings - 2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010 |
ページ | 274-279 |
ページ数 | 6 |
DOI | |
出版ステータス | 出版済み - 2010 |
イベント | 2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010 - Kitakyushu, 日本 継続期間: 12 15 2010 → 12 17 2010 |
その他
その他 | 2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010 |
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Country | 日本 |
City | Kitakyushu |
Period | 12/15/10 → 12/17/10 |
All Science Journal Classification (ASJC) codes
- Computational Theory and Mathematics
- Theoretical Computer Science