支持向量机在供水管网漏水探测中的数据分析及应用探究
Data Analysis and Application Exploration of Support Vector Machine in Leakage Detection of Water Supply Network
宋扬1
作者信息
- 1. 中国建筑材料工业地质勘查中心辽宁总队,辽宁 沈阳 110004
- 折叠
摘要
供水管网漏水是一个普遍存在的问题,长期以来一直困扰着供水系统的安全和可靠性.随着人工智能技术的快速发展和广泛应用,越来越多的研究人员开始将其运用于供水管网漏水探测领域.管网中泄漏的定位信息可以利用管网中各个点的压力或流量值的分布进行确定,然而这是一个复杂的逆向工程问题,本文使用人工智能技术支持向量机(SVM)处理管网中的压力和流量值来获得管网泄漏的位置和大小信息.
Abstract
Water leakage in water supply networks is a common problem that has been troubling the safety and reliability of water supply systems for a long time. With the rapid development and widespread application of artificial intelligence technology,more and more researchers are applying it to the field of water leakage detection in water supply networks. The location information of leaks in the pipeline network can be determined by utilizing the distribution of pressure or flow values at various points in the pipeline network. However,this is a complex reverse engineering problem. This article uses artificial intelligence technology support vector machine ( SVM) to process the pressure and flow values in the pipeline network to obtain the location and size information of leaks in the pipeline network.
关键词
人工智能/支持向量机/供水管网/泄漏/探测分析Key words
artificial intelligence/support vector machine/water supply network/leak/detection analysis引用本文复制引用
出版年
2024
NETL
NSTL
万方数据