Model development in freshwater ecology with a case study using evolutionary computation

Kim, Dong-Kyun;Jeong, Kwang-Seuk;McKay, Robert Ian (Bob);Chon, Tae-Soo;Kim, Hyun-Woo;Joo, Gea-Jae

  • Received : 2010.07.07
  • Accepted : 2010.09.20
  • Published : 2010.12.01


Ecological modeling faces some unique problems in dealing with complex environment-organism relationships, making it one of the toughest domains that might be encountered by a modeler. Newer technologies and ecosystem modeling paradigms have recently been proposed, all as part of a broader effort to reduce the uncertainty in models arising from qualitative and quantitative imperfections in the ecological data. In this paper, evolutionary computation modeling approaches are introduced and proposed as useful modeling tools for ecosystems. The results of our case study support the applicability of an algal predictive model constructed via genetic programming. In conclusion, we propose that evolutionary computation may constitute a powerful tool for the modeling of highly complex objects, such as river ecosystems.


complex river ecosystem;data learning process;ecological modeling;evolutionary computation;phytoplankton proliferation;time-series prediction


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Supported by : Korea Research Foundation