基于SVM的建设项目风险识别方法研究

支持向量机(SVM)是在统计学习理论的基础上发展起来的一种新的机器学习方法。它基于结构风险最小化原则,能有效地解决过学习问题,具有良好的推广性和分类精确性。在项目风险管理中,风险识别是很重要的一个步骤,如果风险不能被识别,那么我们就不能对风险进行转移、控制或管理。针对该问题,本文提出了一种新的风险识别方法-支持向量机,利用该方法对项目风险识别进行了研究,并取得了很好的识别效果。

Study On Risk Identification Method of Construction Project Based On SVM

Support Vector Machine(SVM) is a kind of new machine learning algorithm developed on the basis of statistical learning theory.This algorithm based on the principle of structural risk minimization can solve the problem of overfitting effectively and has good generality capability and better classification accuracy.In the risk management of the project,the risk identification is a very important step.If the risk can't be identified,then we can't shift,control or manage the risk.To this question,we has put forward a kind of new risk identification method,support vector machine.We have studied the project risk by using SVM and have made very good identification result.