Analysing the Impact of Climate Change on The Crop Yields of Irrigated Crops and their Water Requirements in India Using Neuro Evolutionary Algorithm

Global food security, facing the threat of climate change, is one of the major challenges of the 21st century for sustainability that is already under scrutiny with adequate food security for population growth. Current challenges include water shortages, unaffordable costs due to production and demand, and unpredictable weather conditions. They urged farmers to provide improved farming. In particular, uncertainty about climate change, lack of irrigation facilities, lack of land resources, and lack of crops from traditional farming techniques. In agriculture. Different machine learning techniques such as perception, division, regression, and aggregation are used to predict crops. Artificial networks, vector support systems, linear and linguistic lines, decision trees, and Bayesian intelligence are some of the mathematical methods used to implement the prediction. Obviously, choosing the right algorithm for the sample design algorithms presents a challenge for researchers about the selected plants. In this work, research has been conducted on how many algorithms of machine learning can help predict the dissolution of crops. Methods have been developed to generate predictions. Use machine learning technology in a large computer control system.