文章基本信息

标题：IDENTIFICATION OF THE FISH SURVIVAL RATE AND THE FISH TYPES TO LIVE IN LAKE TOBA USING MACHINE LEARNING
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作者：ROMI FADILLAH RAHMAT ; SARAH PURNAMAWATI ; TIFANI ZATA LINI 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2021
卷号：99
期号：10
语种：English
出版社：Journal of Theoretical and Applied
摘要：Waste disposal in Lake Toba conducted by the local citizens has led to water pollution and the decreasing number of freshwater fish. Therefore, the identification of water content is mandatory to ensure the survival and cultivation of the fish in Lake Toba. We conducted two studies using the same data using machine learning methods of Long Short-Term Memory and Support Vector Machine. These studies proved that both methods were reliable in the identification process. The results of this research showed that the water contents in Lake Toba are still good enough for the freshwater fish to live and the types of fish that have to highest chance to survive in Lake Toba.
关键词：Identification;Freshwater Fish;Machine Learning;LSTM;S