Comprehensive evaluation of regulated deficit irrigation using projection pursuit model based on improved double chains quantum genetic algorithm

Due to the incompatibility of irrigation results for single evaluation index and difficulty in evaluating the comprehensive benefit objectively during the process of optimization choice of irrigation schemes, the project pursuit model based on improved double chains quantum genetic algorithm was proposed and applied to the comprehensive evaluation of regulated deficit irrigation. Double chains quantum genetic algorithm was introduced to optimize the projection index function and seek the optimum projection vector, and it was improved by selecting out quantum chromosomes in the search space through the vector distance concentration, gradually optimizing and compressing the search space during the process of evolution. The improved projection pursuit model was applied to comprehensively evaluate deficit irrigation schemes for maize. The results showed that maintaining the level of water deficit 50%-60% of the field capacity at the seedling stage of maize was the best irrigation scheme. Compared with the normal irrigation treatment, the yield was increased by 6.4% and the water use efficiency was increased by 10.8%. Both the global search capability and optimization efficiency of the improved projection pursuit model were significantly improved.