基于改进云模型和Eclat算法的输电线路极端灾害风险评估

针对当前用于输电线路风险评估的云模型中量化等级依靠人为主观划分的不足，提出一种基于改进云模型和Eclat算法的输电线路极端灾害风险评估方法。首先，基于灾害特征信息选取灾害特征因子和典型极端灾害技术要素；通过FCM算法获取一维数据聚类中心，将聚类中心与传统主观云模型数字特征进行结合得到改进后的组合标准云；考虑灾害造成的停运时间、输电线路抗灾能力以及灾害风险的累积效应对数据进行动态修正后，在标准云中进行量化等级划分；最后，应用Eclat算法挖掘量化后的灾害特征因子与风险技术要素间的关联规则，得到风险评估预测模型。实例结果表明，改进后的模型正确率得到提高，获取到的关联规则能够对线路灾害风险进行预测评估。

Extreme Disaster Risk Assessment of Transmission Line Based on Improved Cloud Model and Eclat Algorithm

At present, the cloud model was applied in the transmission line risk assessment. However, there was an insufficiency that the quantified level in the cloud model depended upon factitious and subjective grading. Thus, an extreme disaster risk assessment method of transmission line based on improved cloud model and Eclat algorithm was proposed. Firstly, based on disaster feature information, disaster characteristic factors and technical elements of typical extreme disasters were selected. Secondly, by means of FCM algorithm the one-dimensional data clustering center was obtained, and by use of combining clustering center with digital characteristics of traditional subjective cloud model the improved combined standard cloud was acquired. After the dynamic modification of the data, in which the outage time caused by disaster, the anti-disaster ability of transmission line and the accumulative effect of disaster risk were considered, the grading of the quantified level were performed in the standard cloud. Finally, the Eclat algorithm was applied to mine the association rule between quantified disaster characteristic factors and risk technical elements to obtain the risk assessment forecasting model. Result of instance shows that using the improved cloud model the accuracy of disaster assessment can be improved, and the obtained association rule can be utilized in the forecast assessment on disaster risk of transmission line.