Water Quality Prediction for Salmon Fish Using Gated Recurrent Unit (GRU) Model
Peda Gopi Arepalli, Maheswari Akula, Raga Sruthi Kalli, Akhila Kolli, Vishnu Priya Popuri, Sohitha Chalichama
Abstract
Predicting the quality of water is essential for fish growth and survival. Mainly, yield of aquaculture is depending onthe water conditions. The physical, chemical, and biological parameters that affect the water conditions are PH, Temperature,Dissolved Oxygen, Nitrate, and Biological Oxygen Demand, Mg, EC, Turbidity, Na, PO4, PH, Ca, NO3 and NO2. Previously many studies are focusing on the water quality conditions, but most of the existing systems work on only with one or two water quality parameters and analyse the impact of those parameters for aquaculture. In this paper, we determine the water quality conditions impact on the salmon fishes. Here, gated recurrent unit(GRU) was used to predict the water quality for growth and survival of salmon fish. Proposed GRU algorithm yields the moreaccurate values than the existing ANN and LSTM algorithms.