基于拥挤距离和时空数据挖掘的农田水资源自适应配置算法
An Adaptive Allocation Algorithm of Farmland Water Resources Based on Congestion Distance and Spatiotemporal Data Mining
周爱民1
作者信息
- 1. 巨野县农业农村局,山东 荷泽 274900
- 折叠
摘要
在农田水资源自适应配置过程中,受到环境和水源复杂不确定性的影响,配置算法的计算误差比较明显,需要进一步加强算法的适用性.为此,提出了基于拥挤距离和时空数据挖掘的农田水资源自适应配置算法.利用时空数据挖掘技术从农田的历史供水数据中筛选出关联数据,经过支持度和关联度的计算,获得特征数据集,通过拥挤距离计算公式计算出目标数据的拥挤度,并按照一定顺序排序,在此基础上,计算农田的需水量,确定需水量的上下限,结合拥挤度等参数,建立水资源自适应配置模型,实现农田水资源的灵活配置.实验结果表明:提出的基于拥挤距离和时空数据挖掘的配置算法计算误差小,在水资源利用上,节水效果好,该算法的适用性得到加强.
Abstract
In the process of farmland water resources adaptive allocation,due to the complex uncertainty of environment and water source,the calculation error of the allocation algorithm is obvious,and the applicability of the algorithm needs to be further strengthened.To solve this problem,an adaptive allocation algorithm of farmland water resources based on con-gestion distance and spatiotemporal data mining was proposed.Spatiotemporal data mining technology is used to screen out the associated data from the historical water supply data of farmland,and through the calculation of support degree and cor-relation degree,the characteristic data set is obtained.The crowding degree of the target data is calculated through the crow-ding distance calculation formula,and sorted in a certain order.On this basis,the water demand of farmland is calculated,and the upper and lower limits of water demand are determined.The adaptive allocation model of water resources was estab-lished to realize the flexible allocation of farmland water resources.The experimental results show that the proposed alloca-tion algorithm based on congestion distance and spatiotemporal data mining has small calculation error and good water-saving effect on water resources utilization,and the applicability of the algorithm has been strengthened.
关键词
拥挤距离/时空数据挖掘/农田/水资源/自适应配置Key words
crowding distance/spatio-temporal data mining/farmland/water resources/adaptive configuration引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据