人民黄河2016，Vol.38Issue(7)：130-133,4.DOI:10.3969/j.issn.1000-1379.2016.07.033
RS-SVM模型在大坝安全监控中的应用
Application of RS-SVM Model in Dam Safety Monitoring
孙小冉 1苏怀智 2彭建和1
作者信息
- 1. 安徽 省水利部淮委 水利科学研究院，安徽 蚌埠233000
- 2. 河海大学 水利水电学院，江苏 南京210098
- 折叠
摘要
Abstract
In this paper, the safety monitoring model of small sample, short sequence and uncertainty in dam monitoring sequence was researched by combining rough sets with support vector machines. Using the knowledge reduction in rough sets and introducing the concept of attribute importance to preprocess the input data, it simplified the relationship between influence factors and effect quantity of dam working state and realized the optimization design of input vector of SVM model, which could reflect working mechanism of the dam more explicitly. Taking a concrete dam as an example, the feasibility and characteristics of the RS⁃SVM method was verified respectively by the statistical model, BP neural network model and standard SVM model in the paper.关键词
大坝安全/支持向量机/粗集理论/监控模型Key words
dam safety/support vector machines/rough sets/monitoring model分类
建筑与水利引用本文复制引用
孙小冉,苏怀智,彭建和..RS-SVM模型在大坝安全监控中的应用[J].人民黄河,2016,38(7):130-133,4.
