基于模糊聚类的电力供应链安全风险监测研究

在电力供应链安全风险监测中,针对传统方法下的电力供应链稳定性较低的问题,提出一种基于模糊聚类的电力供应链安全风险监测方法,利用模糊聚类算法对电力供应链中存在的不良数据进行辨识,利用不良数据并结合电力供应链的自身特点,建立基于不良数据的电力供应链安全风险识别模型对电力供应链进行安全风险识别,对安全风险识别数据进行归一化处理与分类处理,实现电力供应链的安全风险监测。为了验证该方法下的电力供应链稳定性,与传统方法进行对比实验,得出结果为该方法与基于决策树规则提取的电力供应链安全风险监测方法、基于稳定特征向量的电力供应链安全风险监测方法、基于Relief算法的电力供应链安全风险监测方法下的电力供应链稳定性分别为86.2%、72.2%、63.3%、42.6%,通过比较可知,该方法能够使电力供应链保持较高的稳定性。

Research on power supply chain security risk monitoring based on fuzzy clustering

In the security risk monitoring of power supply chain,aiming at the problem of low stability of power supply chain under the traditional method,a security risk monitoring method of power supply chain is proposed based on fuzzy clustering.The bad data existing in power supply chain is identified by using the fuzzy clustering algorithm,and a new method based on non-negative data is established combined with the characteristics of power supply chain.The security risk identification model of power supply chain with good data identifies is constructed to indentity the security risk of power supply chain,the security risk identification data is normalized and classitied,and the security risk monitoring of power supply chain is realized.In order to verify the stability of the power supply chain under this method,a comparative experiment with the traditional method is carried out.The results are as follows:the security risk monitoring method of the power supply chain based on decision tree rule extraction,the security risk monitoring method of the power supply chain based on stable eigenvector,and the stability of the power supply chain based on relief algorithm is 86.2%,72.2%,63.3% and 42.6% respectively.The comparison shows that this method can keep the power supply chain stable.