Aquaculture - Water Quality Dataset
Description
This dataset is useful to train and test deep learning models that developed to assess the quality of the water in fish ponds based on the parameters like Temperature, Turbidity, Dissolved Oxygen, Biochemical oxygen demand (BOD), $CO_{2}$, pH, Alkalinity, Hardness, Calcium, Ammonia, Nitrite, Phosphorus, $H_{2}S$ and Plankton. The quality of water in fish ponds is classified in three categories like Excellent, Good and Poor quality. This dataset is prepared based on the threshold values of each input feature for acceptable range, desirable range and stress range for the growth of fishes in ponds. This AWD dataset consists of three different quality samples. They are excellent represented with 0, good quality is labelled with 1 and poor quality id labelled with 2. The developed dataset consists total 1500 poor quality water samples, 1400 excellent quality water samples and 1400 good quality water samples. The developed dataset consists of total 4300 samples with 14 input feature and one output label column.