2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT)最新文献_第6页

A Multi-time Scale Tie-line Energy and Reserve Allocation Model Considering Wind Power Uncertainty for Multi-area System in Hierarchical Control Structure 层次控制结构下考虑风电不确定性的多区域系统多时间尺度联络线能量储备分配模型

2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT) Pub Date : 2021-11-22 DOI: 10.1109/ICESIT53460.2021.9696753

Linyu Wang, Haiyan Jiang, Yibo Jiang

{"title":"A Multi-time Scale Tie-line Energy and Reserve Allocation Model Considering Wind Power Uncertainty for Multi-area System in Hierarchical Control Structure","authors":"Linyu Wang, Haiyan Jiang, Yibo Jiang","doi":"10.1109/ICESIT53460.2021.9696753","DOIUrl":"https://doi.org/10.1109/ICESIT53460.2021.9696753","url":null,"abstract":"Increasing proportion of centralized wind power integrated into partial areas of China leads to requirement in sharing both energy and reserve among areas under its inherent hierarchical control structure, and the unbalance power introduced by wind power uncertainty lead to requirement of correction from day ahead to intra-day along with the improvement of wind power prediction precision. In order to address these problems, this paper develops an information integration method integrating complicated relations among fuel cost, total thermal power output, reserve capacity, owned reserve and expectations of loading shedding and wind curtailment within this area into three types of time-related relation curves in different time scale. Furthermore, a multi-time scale tie-line energy and reserve allocation model is proposed, which contains two levels in control structure, two time scales in dispatch sequence and multiple areas integrated with wind farms. The efficiency of the proposed method is tested in 9-bus test system and IEEE 118-bus system. The results show that cross-regional control centre is able to allocate both energy and reserve among areas efficiently with the integrated relation curves. The proposed model not only relieves energy and reserve shortage in partial areas but also allocates them to more urgent areas in a high effectivity manner in both day-ahead and intraday time scale.","PeriodicalId":164745,"journal":{"name":"2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123283155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An adaptive knowledge distillation algorithm for text classification 一种用于文本分类的自适应知识蒸馏算法

2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT) Pub Date : 2021-11-22 DOI: 10.1109/ICESIT53460.2021.9696948

Zuqin Chen, Tingkai Hu, Chao Chen, Jike Ge, Chengzhi Wu, Wenjun Cheng

{"title":"An adaptive knowledge distillation algorithm for text classification","authors":"Zuqin Chen, Tingkai Hu, Chao Chen, Jike Ge, Chengzhi Wu, Wenjun Cheng","doi":"10.1109/ICESIT53460.2021.9696948","DOIUrl":"https://doi.org/10.1109/ICESIT53460.2021.9696948","url":null,"abstract":"Using knowledge distillation to compress pre-trained models such as Bert has proven to be highly effective in text classification tasks. However, the overhead of tuning parameters manually still hinders their application in practice. To alleviate the cost of manual tuning of parameters in training tasks, inspired by the inverse decrease of the word frequency of TF-IDF, this paper proposes an adaptive knowledge distillation method (AKD). This core idea of the method is based on the Cosine similarity score which is calculated by the probabilistic outputs similarity measurement in two networks. The higher the score, the closer the student model's understanding of knowledge is to the teacher model, and the lower the degree of imitation of the teacher model. On the contrary, we need to increase the degree to which the student model imitates the teacher model. Interestingly, this method can improve distillation model quality. Experimental results show that the proposed method significantly improves the precision, recall and F1 value of text classification tasks. However, training speed of AKD is slightly slower than baseline models. This study provides new insights into knowledge distillation.","PeriodicalId":164745,"journal":{"name":"2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129937823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prediction of Container Throughput in Guangdong Province Based on Different Model 基于不同模型的广东省集装箱吞吐量预测

2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT) Pub Date : 2021-11-22 DOI: 10.1109/ICESIT53460.2021.9696643

Li-Jung Weng

引用次数: 0

Research on Control Strategy of Improved Bidirectional Quasi-Z Source Inverter 改进型双向准z源逆变器控制策略研究

2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT) Pub Date : 2021-11-22 DOI: 10.1109/ICESIT53460.2021.9696744

Huang-Chih Lin, Wei Liang, Lan Zhu, Zhen Cheng, Y. Zheng

引用次数: 0

Research on Anti-Phase Ambiguity Method for High Frame Rate Ultra-Short Baseline Location System 高帧率超短基线定位系统的抗相位模糊方法研究

2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT) Pub Date : 2021-11-22 DOI: 10.1109/ICESIT53460.2021.9696810

Xiaoliang Zhang, Jun-ming Zhang, Jiangqiao Li, Limin Zhang, Nan Zou

引用次数: 0

Application of Natural Gas Pipeline Leakage Detection Based on Improved DRSN-CW 基于改进DRSN-CW的天然气管道泄漏检测应用

2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT) Pub Date : 2021-11-22 DOI: 10.1109/ICESIT53460.2021.9696455

Hongcheng Liao, Wenwen Zhu, Benzhu Zhang, Xiang Zhang, Yu Sun, Cending Wang, Jie Li

引用次数: 1

Computer intelligent recognition and studied of the pronunciation of Xiahe dialect database system through speech aerodynamics 基于语音空气动力学的夏河方言语音数据库系统的计算机智能识别与研究

2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT) Pub Date : 2021-11-22 DOI: 10.1109/ICESIT53460.2021.9696970

Jing Wang, Yonghong Li

引用次数: 0

A Multi-modal Attention-based Seq2eq Model for Predicting Real-estate Prices 基于多模态注意力的房地产价格预测Seq2eq模型

2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT) Pub Date : 2021-11-22 DOI: 10.1109/ICESIT53460.2021.9696701

P. Yao

{"title":"A Multi-modal Attention-based Seq2eq Model for Predicting Real-estate Prices","authors":"P. Yao","doi":"10.1109/ICESIT53460.2021.9696701","DOIUrl":"https://doi.org/10.1109/ICESIT53460.2021.9696701","url":null,"abstract":"Some studies show that the closure and reopening orders brought by covid-19 have had a negative impact on the residential real estate market. Generally speaking, real estate sales decreased significantly during this period, such as office buildings, shopping centers and family houses. Although the overall situation is declining, there are also some new situations. For example, people's desire for spacious family space caused by home office leads to an increase in the demand for large houses in the suburbs. This paper mainly compares the sales differences between suburban family houses and urban family houses in San Francisco and New York in the real estate market during covid-19. The data come from multiple dimensions such as house listing price on the real estate sales website, Machine learning methods could be used for analysis. This paper proposed a multi-modal joint attention seq2seq method to analyze these differences and the reasons for the differences. The experimental results show that one of the possible reasons the house price change in San Francisco is that there are more high-tech job position and their family income is higher than the average level of other regions.","PeriodicalId":164745,"journal":{"name":"2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128871931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Video Anomaly Detection Based on Frame Prediction of Generative Adversarial Network 基于生成对抗网络帧预测的视频异常检测

2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT) Pub Date : 2021-11-22 DOI: 10.1109/ICESIT53460.2021.9696872

Bin Zhao, Boyu Zhao, Pengfei Li

引用次数: 1

Person re-identification algorithm based on multi-module convolutional neural network 基于多模块卷积神经网络的人再识别算法

2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT) Pub Date : 2021-11-22 DOI: 10.1109/ICESIT53460.2021.9696542

Huan Lei, Zeyu Jiao, Junhao Lin, Zaili Chen, Chentong Li, Z. Zhong

{"title":"Person re-identification algorithm based on multi-module convolutional neural network","authors":"Huan Lei, Zeyu Jiao, Junhao Lin, Zaili Chen, Chentong Li, Z. Zhong","doi":"10.1109/ICESIT53460.2021.9696542","DOIUrl":"https://doi.org/10.1109/ICESIT53460.2021.9696542","url":null,"abstract":"For the cross-border tracking needs of target persons in real complex scenes, a person re-identification algorithm based on a multi-module convolution neural network is proposed to solve the problem of person search and matching caused by person scale change, light change, posture change and other factors in the real environment. The algorithm takes ResNet50 as the backbone network of feature extraction. The STN network module is embedded into the backbone network to overcome the impact of person scale change. The IBN network module is integrated for person image color correction to compensate for the influence of illumination change in the real scene. And A person multi-branch feature extraction module is designed to effectively reduce the impact of person posture changes. Through person image feature expression and measurement learning calculation, person similarity matching across cameras is realized. Experiments show that this method has good performance in real complex scene test data, and its Rank-1 and mAP are 98.30% and 95.78% respectively. It can be used for person matching and search in a real complex environment, and has certain practical value.","PeriodicalId":164745,"journal":{"name":"2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116310655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0