International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Movement Pattern Recognition of Medaka for an Insecticide: A Comparison of Decision Tree and Neural Network

  • Kim, Youn-Tae (School of Electrical and Computer Eng., Pusan National University) ;
  • Park, Dae-Hoon (School of Electrical and Computer Eng., Pusan National University) ;
  • Kim, Sung-Shin (School of Electrical and Computer Eng., Pusan National University)
  • Published : 2007.03.01
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Abstract

Behavioral sequences of the medaka (Oryzias latipes) were continuously investigated through an automatic image recognition system in response to medaka treated with the insecticide and medaka not treated with the insecticide, diazinon (0.1 mg/l) during a 1 hour period. The observation of behavior through the movement tracking program showed many patterns of the medaka. After much observation, behavioral patterns were divided into four basic patterns: active-smooth, active-shaking, inactive-smooth, and inactive-shaking. The "smooth" and "shaking" patterns were shown as normal movement behavior. However, the "shaking" pattern was more frequently observed than the "smooth" pattern in medaka specimens that were treated with insecticide. Each pattern was classified using classification methods after the feature choice. It provides a natural way to incorporate prior knowledge from human experts in fish behavior and contains the information in a logical expression tree. The main focus of this study was. to determine whether the decision tree could be useful for interpreting and classifying behavior patterns of the medaka.

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References

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