基于粗集和神经网络融合法对大坝病变成因分析的研究与探索

Dam Disease Analysis of the Research and Exploration Based on Rough Sets and Neural Networks

大坝病变成因挖掘是大坝安全管理的重要基础,是大坝病变识别的前提。在病变分析识别中,由于大坝的工作条件比较复杂、病变模式和机理各不相同,常用的分析诊断方法很难实现大坝病变成因挖掘,因此本文将通过分析粗集理论和人工神经网络各自在信息挖掘应用中的优缺点,提出粗集和神经网络融合的算法,并将该算法运用到大坝病变成因挖掘中。

The excavation of darn deformation is an the important foundation of dam safety management and the premise of dam disease identification. In lesion analysis and identification, As the working conditions of the dam are complex, the modes and mechanisms of the disease vary, The common analysis and diagnosis methods are difficult to excavate the cause of dam disease, This article goes through the analysis of rough set theory and artificial neural network in their respective advantages and disadvantages in the application of data mining, the rough set and neural network fusion algorithm, and the algorithm is applied to mining dam disease causes.