摘要
水资源问题已经成为令世界苦恼的全球性危机问题。随着当今社会经济的高速发展、人口剧增、现代化以及城市化的进程不断加快,各行业用水的需求量逐渐升高,水资源短缺、水资源浪费等问题日益严峻。黑龙江省是中国重要的工业基地、产粮大省,随着经济社会的快速发展,水资源供需矛盾日益凸显,虽然已采取多项措施对水资源进行保护,但水资源开发利用形势依然严峻。针对以上问题,建立了粒子群算法(PSO)优化的支持向量机(SVM)模型对黑龙江省水资源承载力进行评价,结合黑龙江省实际情况建立评价指标体系、指标分级标准,对黑龙江省2020年13个地市水资源承载力进行评价,为日后水资源开发利用作出参考,对支持向量机在水资源方面的应用推广起到一定的意义,并且PSO-SVM模型补充了多因素综合评价相关理论。
The problem of water resources has triggered a global crisis.With the rapid development of the social economy,the rapid increase in population,and the acceleration of modernization and urbanization,the demand for water in various industries is gradually increasing,and the problems of water shortage and water waste are becoming serious.Heilongjiang Province is an important industrial base and a major grain-producing province in China.With the rapid development of the economy and society,the contradiction between the supply and demand of water resources has become increasingly prominent.Although many measures have been taken to protect water resources in Heilongjiang Province,the development and utilization situation of water resources is still severe.In view of the above problems,this paper established a support vector machine(SVM)model optimized by particle swarm optimization(PSO)algorithm to evaluate the water resources carrying capacity in Heilongjiang Province.Based on the actual situation of Heilongjiang Province,an evaluation index system and index grading standards were established to evaluate the water resources carrying capacity of 13 cities in Heilongjiang Province in 2020.It thus provides a reference for the development and utilization of water resources in the future and plays a certain role in the application and promotion of SVM in water resources.The PSO-SVM model complements the theory of multi-factor comprehensive evaluation.
作者
王涛
李治军
WANG Tao;LI Zhijun(College of Water Resources and Electric Engineering,Heilongjiang University,Harbin 150080,China;Cold Groundwater Research Institute,Heilongjiang University,Harbin 150080,China)
出处
《人民珠江》
2023年第9期51-60,68,共11页
Pearl River
基金
“十二五”国家科技支撑计划课题(2014BAD12B01-03)。
关键词
水资源承载力
粒子群算法
支持向量机
黑龙江
water resources carrying capacity
particle swarm optimization algorithm
support vector machine
Heilongjiang
