In order to improve the accuracy of power dispatch professional language understanding, the professional language understanding method of power dispatching based on multi-model fusion is proposed. First, the dispatch professional language is represented as a low-dimensional feature vector based on the pre-trained word vector model. Then the mapping relationship between scheduling professional language and scheduling intention is trained based on text convolutional neural network (TextCNN). The relation relationship between professional language slot feature and information labels are trained based on the bidirectional long-term short-term memory network-conditional random field (BiLSTM-CRF), the dispatch professional language understanding is realized by the joint multi-model recognition results. Finally, through the verification of power dispatch professional language of a control center, compared with other methods, the proposed professional language understanding method has higher accuracy.
In order to improve the online application ability and auxiliary decision-making ability of power grid dispatching operation rules, a method for identifying key information of dispatching operation rules based on Bidirectional Long Short-Term Memory network-Conditional Random Field (BiLSTM-CRF) is proposed. A method for feature extraction and feature labeling of dispatching operation rule text is proposed, and BiLSTM is used to learn nonlinear characteristics and implicit timing information between regular text features, and CRF is used to optimize bidirectional network encoding labels globally. The recognized rule text information is combined according to the definition level to form a knowledge graph of dispatching operation rules. Through the verification of the power grid operation rules of a control center, compared with other methods, the proposed model recognizes the average precision rate, recall rate and F1 value of 98.10%, 98.19% and 98.10%, respectively, which can more accurately support the refined retrieval and positioning of the text of the dispatching operation rules.
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