Irrigation water resource optimization configuration method based on bi-objective immune particle swarm algorithm

Abstract

The invention provides an irrigation water resource optimization configuration method based on a bi-objective immune particle swarm algorithm. Crops cannot grow under sufficient irrigation due to inadequate irrigation water in arid regions, the analysis of the crop growth characteristics and the rational distribution of water resources allow the crops to achieve optimum yields even in drought conditions. The optimization method is an immune particle swarm optimization algorithm based on congestion distance, simulates the antibodies and mutation mechanisms of the human immune system, improves the conventional particle swarm algorithm, selects a part of the new generation of particle swarm based on the congestion distance to be an antibody population, and then selects an antibody from the antibody population to cross and mutate the particles. The method is capable of carrying out reasonable water distribution during the growing season of the crops so as to maximize the yield of crops while minimizing the amount of irrigation water.

Description

technical field [0001] The invention relates to a dual-objective immune particle swarm algorithm, which is improved by adding crowding distance and immunity to the particle swarm algorithm to solve the problem of water resource allocation in the crop growth period under the condition of water shortage in arid areas, and belongs to the field of agricultural irrigation. Background technique [0002] my country is a country with severe drought and water shortage. Due to the continuous growth of our population, the continuous expansion of industrialization development, and the environmental pollution caused by human activities, water resources are becoming more and more scarce. my country is a large agricultural country, and agricultural water consumption accounts for the vast majority of the total water consumption. However, even so, there are still many farmlands in our country that do not have enough water for irrigation. The lack of water resources makes it impossible for cro...

AI Technical Summary

Problems solved by technology

[0007] The particle swarm optimization algorithm achieves the overall particle optimum by pursuing the individual extremum and the global extremum, and the convergence speed is fast. Unable to jump out, the optimization result is not very ideal. In this chapter, the concepts of crowding distance and immunity are added, and an improved particle swarm optimization algorithm is proposed to avoid excessive aggregation of particles, and the optimized non-inferior solution set is better

Images