Yufeng Wang

TL;DR: In this article , a wind turbine spindle fault state prediction model based on fusion structure is proposed, which can more fully mine the information representation of wind turbine status, and the fusion structure model effectively fuses the features of the three modules.

TL;DR: Zhang et al. as mentioned in this paper proposed an abstractive text summarization model based on bidirectional encoder representations from transformers (BERT) vectorization, which helps the subsequent encoder and decoder to fuse the full-text information to generate a summary with high generality.

TL;DR: This article proposed a Chinese event extraction method RoformerFC (Roformer model with FGM and CRF) based on the Roformer model to address the problems of the current event extraction field, which still suffers from errors in the pretraining and fine-tuning stages, inability to directly handle texts with more than 512 tokens, and inaccurate event extraction due to insufficient semantic sample diversity.

TL;DR: In this article , a hierarchical decomposition-based Chinese event element extraction model is proposed to improve the performance of event element detection. But the model is not suitable for long text, the errors of pre-training and fine-tuning stages, and the single sample of semantic features.