A Design and Implementation Red Tide Prediction Monitoring System using Case Based Reasoning 


Vol. 35,  No. 12, pp. 1819-1826, Dec.  2010


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  Abstract

It is necessary to implementation of system contain intelligent decision making algorithm because discriminant and prediction system for Red Tide is insufficient development and the study of red tide are focused for the investigation of chemical and biological causing. In this paper, we designed inference system using case based reasoning method and implemented knowledge base that case for Red Tide. We used K-Nearest Neighbor algorithm for recommend best similar case and input 375 EA by case for Red Tide case base. As a result, conducted 10-fold cross verification for minimal impact from learning data and acquired confidence, we obtained about 84.2% average accuracy for Red Tide case and the best performance results in case by number of similarity classification k is 5. And, we implemented Red Tide monitoring system using inference result.

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  Cite this article

[IEEE Style]

B. Song, M. Jung, S. Lee, "A Design and Implementation Red Tide Prediction Monitoring System using Case Based Reasoning," The Journal of Korean Institute of Communications and Information Sciences, vol. 35, no. 12, pp. 1819-1826, 2010. DOI: .

[ACM Style]

Byoung-Ho Song, Min-A Jung, and Sung-ro Lee. 2010. A Design and Implementation Red Tide Prediction Monitoring System using Case Based Reasoning. The Journal of Korean Institute of Communications and Information Sciences, 35, 12, (2010), 1819-1826. DOI: .

[KICS Style]

Byoung-Ho Song, Min-A Jung, Sung-ro Lee, "A Design and Implementation Red Tide Prediction Monitoring System using Case Based Reasoning," The Journal of Korean Institute of Communications and Information Sciences, vol. 35, no. 12, pp. 1819-1826, 12. 2010.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880