期刊名称：TELKOMNIKA (Telecommunication Computing Electronics and Control)
印刷版ISSN：2302-9293
出版年度：2019
卷号：17
期号：1
页码：226-234
DOI：10.12928/telkomnika.v17i1.11605
出版社：Universitas Ahmad Dahlan
摘要：Upwelling is a natural phenomenon related with the increase in water mass that also occurs in
Maninjau Lake, West Sumatra. The upwelling phenomenon resulted in considerable losses for freshwater
fish farming because make mass mortalities of fish in farming using the method of floating net cages
(karamba jaring apung/KJA). It takes a system that can predict the possibility of upwelling as an early
warning to the community, especially fish farming to immediately prepare early anticipation of upwelling
prevention. With historical water quality monitoring data at six sites in Maninjau Lake for 17 years, a
prediction model can be made. There are three input criteria for Tsukamoto FIS that is water temperature,
pH, and dissolve oxygen (DO). The model is built with fuzzy logic integration with the genetic algorithm to
optimize the membership function boundaries of input and output criteria. After the optimization, hybrid
Tsukamoto FIS and genetic algorithm successfully make a correct upwelling prediction on of 16 data with
94% accuracy.
其他摘要：Upwelling is a natural phenomenon related with the increase in water mass that also occurs in Maninjau Lake, West Sumatra. The upwelling phenomenon resulted in considerable losses for freshwater fish farming because make mass mortalities of fish in farming using the method of floating net cages (karamba jaring apung/KJA). It takes a system that can predict the possibility of upwelling as an early warning to the community, especially fish farming to immediately prepare early anticipation of upwelling prevention. With historical water quality monitoring data at six sites in Maninjau Lake for 17 years, a prediction model can be made. There are three input criteria for Tsukamoto FIS that is water temperature, pH, and dissolve oxygen (DO). The model is built with fuzzy logic integration with the genetic algorithm to optimize the membership function boundaries of input and output criteria. After the optimization, hybrid Tsukamoto FIS and genetic algorithm successfully make a correct upwelling prediction on of 16 data with 94% accuracy.
关键词：floating net cages;hybrid FIS-GA;maninjau lake;prediction;upwelling
