Conference on Electronic Information Engineering and Data Processing最新文献

Scene text detection with gradient guidance 场景文本检测与梯度引导

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682595

Siyu Chen, Enqi Zhan, Manjie Zhang

引用次数: 0

Prairie mouse hole target detection technology based on deep learning 基于深度学习的大鼠洞目标检测技术

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682261

C. Li, Xiaoling Luo

引用次数: 0

CNN-BiLSTM sewage treatment dissolved oxygen concentration prediction model based on attention mechanism CNN-BiLSTM基于注意力机制的污水处理溶解氧浓度预测模型

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682282

Wenbo Zhang, Jun Xie, Xinxiu Liu, Langlang Zhang, Pan Geng

{"title":"CNN-BiLSTM sewage treatment dissolved oxygen concentration prediction model based on attention mechanism","authors":"Wenbo Zhang, Jun Xie, Xinxiu Liu, Langlang Zhang, Pan Geng","doi":"10.1117/12.2682282","DOIUrl":"https://doi.org/10.1117/12.2682282","url":null,"abstract":"Aiming at the characteristics of complex biochemical reaction, nonlinearity and difficult prediction of dissolved oxygen in sewage treatment process, this paper proposes a dissolved oxygen concentration prediction model based on CNN-BiLSTM hybrid artificial neural network. Firstly, the abnormal data is identified and eliminated by data preprocessing, and the missing data is filled by interpolation method. Then, the Pearson correlation coefficient is used to analyze the correlation between dissolved oxygen and other variables. Multiple variable data with good correlation are selected and input into the CNN-BiLSTM network model. The dissolved oxygen concentration is predicted by CNN convolution operation combined with bidirectional long-term and short-term memory neural network (Bi-LSTM), and the time attention mechanism is introduced to learn the weight distribution between different time steps, focusing on the time step that has the greatest impact on dissolved oxygen concentration, so as to improve the prediction accuracy of the model. Compared with LSTM, GRU, CNN-LSTM and CNN-GRU models, the simulation results show that the proposed model can predict the dissolved oxygen more accurately and has higher prediction accuracy.","PeriodicalId":177416,"journal":{"name":"Conference on Electronic Information Engineering and Data Processing","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122048426","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

Fault diagnosis of three-level active power filter based on hybrid logic model 基于混合逻辑模型的三电平有源电力滤波器故障诊断

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682383

Zhenhai Zhang, L. Niu, Lei Wang, Hongbo Li, Xiaoyu He, Yanqiang Zhai

引用次数: 0

RGB-D SLAM in dynamic environments with deep learning 基于深度学习的动态环境RGB-D SLAM

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682598

W. Chen, Deji Li

引用次数: 0

Reinforced model-agnostic counterfactual explanations for recommender systems 推荐系统的强化模型不可知论反事实解释

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682249

Ao Chang, Qingxian Wang

引用次数: 0

Analysis of seismic anomalies in northern state of New Zealand based on Schumann resonance time-frequency diagram 基于Schumann共振时频图的新西兰北部地震异常分析

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682266

Mingyi Que, Yongming Huang, Yong Lu

{"title":"Analysis of seismic anomalies in northern state of New Zealand based on Schumann resonance time-frequency diagram","authors":"Mingyi Que, Yongming Huang, Yong Lu","doi":"10.1117/12.2682266","DOIUrl":"https://doi.org/10.1117/12.2682266","url":null,"abstract":"Schumann resonance is a phenomenon in the extremely low frequency electromagnetic field, which is generally presented in the form of spectrum diagram and time-frequency diagram in the form of data. In this paper, based on the analysis of the data of Schumann resonance 0~50Hz time-frequency diagram, the time difference matrix and frequency difference matrix of the first and second order of the Schumann resonance time-frequency diagram are extracted respectively, and the time-frequency diagram is encoded and decoded by convolution autoencoder. In the process of encoding and decoding, the mapping function is constructed by combining the constraints, and the time-frequency diagram is decomposed and fitted, so as to improve the ability of data to reflect changes. Then, according to the seven different index matrices obtained, the determinant, rank and trace of each index matrix are obtained, and the earthquakes with magnitude above six in the northern state of New Zealand from 2016 to 2019 are analyzed. The final experimental results show that there is a certain degree of feedback phenomenon in the selected analysis indicators in the research object of this paper for a period of time before and after the event, which shows that the method of time-frequency diagram analysis is feasible.","PeriodicalId":177416,"journal":{"name":"Conference on Electronic Information Engineering and Data Processing","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132460406","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

Multi-feature extraction network cross-resolution person re-identification based on SR technology 基于SR技术的多特征提取网络交叉分辨率人物再识别

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682284

Run-Lan Tian, Zongzong Wu, Qingwei Pang, Jian Zheng

引用次数: 0

Two-stage attentional temporal convolution and LSTM model for financial data forecasting 两阶段注意时间卷积和LSTM模型用于金融数据预测

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682556

Lifang Chen, Xiaowan Li, Zhenping Xie

{"title":"Two-stage attentional temporal convolution and LSTM model for financial data forecasting","authors":"Lifang Chen, Xiaowan Li, Zhenping Xie","doi":"10.1117/12.2682556","DOIUrl":"https://doi.org/10.1117/12.2682556","url":null,"abstract":"Financial time series usually consist of multiple time series, and financial time series data forecasting models use the historical data plays of multiple driving series to predict the future values of the target series. In recent years, attention-based Long and Short-Term Memory (LSTM) neural networks and Temporal Convolutional Networks (TCN) have been widely used in time series forecasting. In this paper, we propose a two-stage attention-based TCN and LSTM hybrid forecasting model, in order to better obtain the spatial correlation of driving sequences, we used causal self-attention to obtain the spatial attention weights of driving sequences, then use TCN to extract the short-term features of the series in the first stage, in the second stage, adding the temporal attention module computes the sequence adaptively assigning weights to the input sequence for the current and historical moments, and finally use LSTM to capture the long-term dependence of the time-series data. We used the NASDAQ 100 stock dataset and the financial time series of CSI 300 companies to measure the performance of the proposed model in financial data forecasting.","PeriodicalId":177416,"journal":{"name":"Conference on Electronic Information Engineering and Data Processing","volume":"12700 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131120594","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

Optimal scheduling of virtual power plant considering demand side response 考虑需求侧响应的虚拟电厂最优调度

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682490

Haolin Sun, Anni Wang, Zijian Gao, Juan Liu, Jia Cui, Jiazheng Tian, C. Li

{"title":"Optimal scheduling of virtual power plant considering demand side response","authors":"Haolin Sun, Anni Wang, Zijian Gao, Juan Liu, Jia Cui, Jiazheng Tian, C. Li","doi":"10.1117/12.2682490","DOIUrl":"https://doi.org/10.1117/12.2682490","url":null,"abstract":"In this paper, a virtual power plant model considering demand side response is proposed. Considering the influence of price demand-side response on virtual power plant, an optimal scheduling control method was proposed for virtual power plant, which included demand-side response, wind power, photovoltaic, gas turbine and energy storage equipment. Firstly, a mathematical model was built with the maximum net income of virtual power plant as the objective function. Secondly, a reasonable operation strategy was designed. The demand-side response strategy was optimized based on wind-landscape output prediction. Thirdly, the gas turbine and energy storage equipment coordinated the output allocation to compensate the deviation between the actual output and the predicted output of the scenery. Finally, through the simulation analysis of the example, the results show that the consideration of the demand-side response based on price in the virtual power plant can standardize the user's electricity consumption. And the load peaking and valley filling effect is obvious. The designed operation strategy has coordinated the power distribution of various energy sources and maximized the income of the virtual power plant.","PeriodicalId":177416,"journal":{"name":"Conference on Electronic Information Engineering and Data Processing","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133745802","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: 1