基于神经网络的定值名称智能比对方法
摘要：保护定值的正确性对充分发挥继电保护系统的作用至关重要，但目前定值比对仍采用人工方式，工作量大、时间长且结果正确性无法保证。对此，梳理了定值名称的命名特点，提出了一种基于神经网络的继电保护定值名称智能比对方法。首先进行文本预处理，然后将预处理后的定值文本向量化，最后使用双向长短时记忆(bi-directional long short-term memory, Bi-LSTM)神经网络计算定值名称语义特征向量相似度。算例表明，基于神经网络的定值名称智能比对方法能有效完成定值单和运行定值名称的匹配，且神经网络比模糊匹配处理定值名称匹配问题准确率更高，速度更快。
Abstract:The correctness of the protection setting is of great importance to make full use of the relay protection system, but current setting comparison still uses manual methods, which requires heavy workload, and consumes long time, however the correctness of the results cannot be guaranteed. For this reason, the naming characteristics of the setting value name were sorted out, and a neural network-based intelligent comparison method for the setting value names of relay protection was proposed. Firstly, the text preprocessing was performed. Secondly, the preprocessed setting value text was vectorized. Finally, the bi-directional long short-term memory (Bi-LSTM) neural network was utilized to calculate the similarity of semantic feature vectors of the setting value name. Results of computing example show that the intelligent comparison method of setting value name based on neural network can effectively complete the matching of setting value list and running fixed value name, and comparing with fuzzy matching the neural network possesses higher accuracy and faster speed in handling setting value name matching problem.
标题：基于神经网络的定值名称智能比对方法
英文标题：Intelligent Comparison Method of Setting Value Name Based on Neural Network
作者：曹海欧, 崔玉, 易新, 李萍, 朱鹏宇, 李金铄, 戴志辉,
关键词：定值名称, 文本相似度, 双向长短时记忆(Bi-LSTM), 分布式表示, 词向量,
发表日期：2023-08-10
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