NLP-assisted information extraction for layout criteria of substation

Bing Wu; Yuanbin Song; Jinhao Cao

doi:10.1117/12.2683030

16 June 2023 NLP-assisted information extraction for layout criteria of substation

Bing Wu, Yuanbin Song, Jinhao Cao

Author Affiliations +

Proceedings Volume 12703, Sixth International Conference on Intelligent Computing, Communication, and Devices (ICCD 2023); 127030G (2023) https://doi.org/10.1117/12.2683030
Event: Sixth International Conference on Intelligent Computing, Communication, and Devices (ICCD 2023), 2023, Hong Kong, China

Abstract

The automatic compliance review of substation design model greatly depends on the computer-understandable layout criteria. Unfortunately, most of these layout criteria are depicted in a series of design codes written in natural language. Meanwhile manual conversion from unstructured code text to layout rules is often costly and time consuming. In this regard, automatic extracting layout information can be developed utilizing Natural Language Processing (NLP) tools based on deep learning. The layout texts are collected and manually labeled to establish the experimental corpus for further study, and then the NLP-assisted information extraction method is developed mainly using the Bidirectional Long Short-Term Memory (BiLSTM) networks and Conditional Random Field (CRF). Finally, the information extraction model is trained on the labeled experimental corpus. The test results indicate that the developed model is feasible to extract semantic information of layout constraints residing in design code.

Citation Download Citation

Bing Wu, Yuanbin Song, and Jinhao Cao "NLP-assisted information extraction for layout criteria of substation", Proc. SPIE 12703, Sixth International Conference on Intelligent Computing, Communication, and Devices (ICCD 2023), 127030G (16 June 2023); https://doi.org/10.1117/12.2683030

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