Precision irrigation decision-making support by using an improved genetic algorithm

The aim of the paper is to find the optimal solution for field precision irrigation through an improved genetic algorithm in which the intermediate results were retained and calculated separately. The possibility of working out the optimal solution was increased by comparing the present optimal solution with the new results. Taking the factors such as the climate and the terrain into consideration, the improved algorithm was applied to an experiment in the paper. The experiment data were collected from Xiaotangshan farmland and the constraints of the algorithm were set according to the field's basic data, historical data and the computing conditions. The improved genetic algorithm was applied to the decision-making of the irrigation. Finally, software with user-friendly interface was built using WebGIS technology. By using the software, the users could intuitively understand and operate the entire decision-making process. This study shows that the improved genetic algorithm can significantly speed up the search of the optimal solution and the efficiency of field irrigation decision-making.