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AN EARLY-WARNING MODEL OF DAM SAFETY BASED ON ROUGH SET THEORY AND SUPPORT VECTOR MACHINE

机译:基于粗糙集理论和支持向量机的大坝安全预警模型

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摘要

There are strong non-linear and dynamic relations between dam behavior and its influence factors. The early-warning models of dam safety need to be described with non-linear function. Rough set theory is used to implement data pretreatment on dam safety monitoring. Main factors influencing dam safety are mined. An early-warning model is built with support vector machine. The proposed model can provide an effective performance of approximation and forecast for the relations between dam behavior and above mined factors. The system rule on dam behaviors can be learned and induced from the prototype observations of dam safety. The expression and parameters of early-warning model need not to be predefined.
机译:大坝行为与其影响因素之间存在强烈的非线性和动态关系。需要使用非线性功能来描述大坝安全的预警模型。粗糙集理论用于实施水坝安全监测的数据预处理。影响大坝安全的主要因素是开采的。使用支持向量机建立了预警模型。所提出的模型可以提供有效的近似和预测的近似和预测,以实现水坝行为与上述因素之间的关系。可以从大坝安全的原型观察中学习和诱导大坝行为的系统规则。早期预警模型的表达和参数不需要预定义。

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