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基于C4.5决策树的电网故障设备状态评估

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对电网故障设备进行准确的状态评估可有效提高产品质量,减少资源浪费.提出了一种基于C4.5决策树的电网故障设备状态评估方法.首先,通过对电网设备故障因素进行分析,构建了包含13个状态量的设备故障状态体系.其次,基于C4.5决策树算法构建了电网设备状态评估模型.最后,通过后剪枝算法对模型进行剪枝降低模型复杂度,并定义多项指标对算法模型进行评价.实际数据分析结果表明,构建的算法模型预测准确率、精确率均能够达到91%以上,有效支撑设备厂商储备备品备件方面工作,提升企业效益.
Condition Evaluation of Power Grid Fault Equipment Based on C4.5 Decision Tree
In this paper,a method of power system fault equipment status evaluation based on C4.5 decision tree is proposed.First of all,by analyzing the fault factors of power grid equipment,a state system of equipment fault quantity in-cluding 13 state quantities is constructed.Secondly,based on C4.5 decision tree algorithm,the power grid equipment sta-tus evaluation model is constructed.Finally,the post-pruning algorithm is used to prune the model to reduce the complexi-ty of the model,and multiple indicators are defined to evaluate the algorithm model.The actual data analysis results show that the prediction accuracy and accuracy of the algorithm model built in this paper can reach more than 91%,effectively supporting the work of equipment manufacturers in the storage of spare parts,and improving enterprise efficiency.

C4.5 decision treefaulty equipmentstatus assessmentpruneevaluating indicator

刘正超、邹文仲、杜蕊妍

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南京南瑞继保电气有限公司,江苏 南京 211102

南京师范大学泰州学院,江苏泰州 225300

C4.5决策树 故障设备 状态评估 剪枝 评价指标

2024

工业控制计算机
中国计算机学会工业控制计算机专业委员会 江苏省计算技术研究所有限责任公司

工业控制计算机

影响因子:0.258
ISSN:1001-182X
年,卷(期):2024.37(3)
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