基于粒子群算法的农业水资源需求预测

Wen-long Yi
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引用次数: 2

摘要

水资源的规划与管理越来越重要,需水量预测作为整个规划的前提和基础,已成为农业发展中一项非常重要的任务。结合粒子群算法构建农业水资源需求预测模型,分析了传统粒子群算法的不足,并对量子粒子群算法进行了适当的改进。在此基础上构建了基于水资源需求预测的农业水资源需求预测模型的功能结构,并分析了粒子群算法在本文系统中的应用过程。模型构建完成后,对模型的性能进行验证,并设计仿真试验,用实际数据评价系统预测的效果。同时,利用本文构建的模型对水资源预测需求的影响因素进行了分析。从实验分析的结果可以看出,本文构建的模型对于水资源需求的预测更为有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forecast of agricultural water resources demand based on particle swarm algorithm
ABSTRACT The planning and management of water resources are becoming more and more important, and the forecast of water demand as the prerequisite and foundation of the entire planning has become a very important task in agricultural development. This paper combines the particle swarm algorithm to construct the agricultural water resource demand forecasting model, analyzes the shortcomings of the traditional particle swarm algorithm, and makes appropriate improvements to the quantum particle swarm algorithm. Moreover, this paper constructs the functional structure of the agricultural water resource demand forecast model based on the forecast demand of water resources, and analyzes the application process of the particle swarm algorithm in the system of this paper. After the model is constructed, the performance of the model is verified, and the simulation test is designed to evaluate the effect of system forecast with actual data. At the same time, this paper uses the model constructed in this paper to analyze the factors affecting water resources forecast demand. From the results of the experimental analysis, it can be seen that the model constructed in this paper is more effective in the forecast of water resources demand.
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