Comprehensive evaluation of integrative drip-irrigation and fertilization using a projection pursuit model based on the improved double chains quantum genetic algorithm
Wang, B.; Li, Y.; Meng, Y.; Liu, X.
Desalination and Water Treatment 66: 229-234
2017
ISSN/ISBN: 1944-3994 Accession: 070811001
Finding the optimal solution in a single-treatment drip-irrigation and fertilizer scheme is nontrivial because of the inherent difficulty in evaluating the overall benefit of such a scheme. To address this problem, we have developed the project pursuit model based on the improved double chains quantum genetic algorithm, and applied it to integrative drip-irrigation and fertilization. The double chains quantum genetic algorithm was introduced to optimize the projection index function and seek the optimum projection vector. This algorithm was improved by introducing an immunity operator, a simulated annealing operator, and gradually optimizing and compressing the quantum chromosome search space during the evolution process. The improved projection pursuit model was applied to maize cultivation. The results show that the optimization efficiency and global search capability improved substantially. Increased nitrogen splits promoted dry matter above ground and nitrogen uptake in the maize, and also improved the yield and the plumping of seeds. A management practice of 150-200 kg/hm(2) of nitrogen applied at three splits produced the highest production in integrative drip-irrigation and fertilizer schemes for the black soil in Northeast China.