Description

Water quality prediction (WQP) plays an essential role in water quality management for aquaculture to make aquaculture production profitable and sustainable. Water quality is affected by many factors, such as fish density, quality of the feed, feeding interval, climate, and more. The change in water quality will upset the balance of the system with algae bloom, bacterial growth, etc. To maintain and manage aquaculture, water quality monitoring and water quality prediction (WQP) are essential. In aquaculture, water quality is the most influential and critical factor that affects production as well as product quality. The vital water quality parameters in aquaculture are salinity, pH, dissolved oxygen (DO), and temperature. The system is developed the different deep and machine learning algorithm for predicting the water quality either the water is safe or not such as CNN with LSTM, CNN with GRU and logistic regression. Then, finally we will estimate some performance metrics such as MAE, MSE, RMSE and MAPE.