A Review on Artificial intelligence Algorithms and Machine Learning to Predict the Quality of Groundwater for Irrigation Purposes

Utilising ordinary techniques to predict the irrigation water quality is generally costly and difficult for Farmers, especially for emerging countries. Moreover, machine learning and ANN algorithms are emerging technologies implemented in many countries nowadays. To overcome the issues for predicting and evaluating water quality indices in irrigation water, we need to analyse the efficient algorithms. There are several implemented models to predict the water quality parameters, and this study has been analysed various machine learning algorithms and ANN models. Finally concluded with an efficient developed approach that has been useful for the farmers in minimal expense and real-time forecasting of groundwater quality. The Water Quality Index (WQI) is the most basic indicator to distinguish underground water quality. Finally, insight calculations are utilised to streamline the boundaries of participation capabilities in the ANN model to promote the expectation of precision