2023 Asia-Europe Conference on Electronics, Data Processing and Informatics (ACEDPI)最新文献_第10页

Automotive Supply Chain Logistics Management System Based on IOT Technology 基于物联网技术的汽车供应链物流管理系统

2023 Asia-Europe Conference on Electronics, Data Processing and Informatics (ACEDPI) Pub Date : 2023-04-01 DOI: 10.1109/ACEDPI58926.2023.00081

R. Tian

引用次数: 0

Analysis of Interval Flow Calculation Algorithm of Multi-Loop Complex Power Network Based on Knowledge Mapping 基于知识映射的多回路复杂电网区间潮流计算算法分析

2023 Asia-Europe Conference on Electronics, Data Processing and Informatics (ACEDPI) Pub Date : 2023-04-01 DOI: 10.1109/ACEDPI58926.2023.00096

Y. Wang

{"title":"Analysis of Interval Flow Calculation Algorithm of Multi-Loop Complex Power Network Based on Knowledge Mapping","authors":"Y. Wang","doi":"10.1109/ACEDPI58926.2023.00096","DOIUrl":"https://doi.org/10.1109/ACEDPI58926.2023.00096","url":null,"abstract":"The continuous integration of high proportion of new energy into the power grid has exacerbated the complexity of the uncertainty of the power system, making the traditional single-point deterministic power flow calculation increasingly difficult to meet the needs of power system planning and dispatching. Interval power flow is an uncertain power flow calculation method based on interval algorithm, which is characterized by only paying attention to the boundary information of the uncertainty, and is especially suitable for the uncertain power flow calculation of high proportion and high permeability new energy connected to the grid. This paper analyzes the shortcomings of the existing mainstream knowledge representation forms for the expression ability of artificial empirical knowledge of power flow adjustment, fully considers the characteristics of the combination of qualitative knowledge and quantitative knowledge in the artificial empirical knowledge required in the process of power flow adjustment, and the combination of related knowledge and rational knowledge, and constructs a knowledge map in the field of power flow adjustment.","PeriodicalId":124469,"journal":{"name":"2023 Asia-Europe Conference on Electronics, Data Processing and Informatics (ACEDPI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130265147","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

Design of Oil Painting Damaged Area Repair Algorithm Based on Convolution Neural Network 基于卷积神经网络的油画破损区域修复算法设计

2023 Asia-Europe Conference on Electronics, Data Processing and Informatics (ACEDPI) Pub Date : 2023-04-01 DOI: 10.1109/ACEDPI58926.2023.00026

Yaling Dang

{"title":"Design of Oil Painting Damaged Area Repair Algorithm Based on Convolution Neural Network","authors":"Yaling Dang","doi":"10.1109/ACEDPI58926.2023.00026","DOIUrl":"https://doi.org/10.1109/ACEDPI58926.2023.00026","url":null,"abstract":"Oil painting has been introduced into China for nearly a century. In recent decades, the introduction of the concept and technique of oil painting in Europe has lagged far behind, but the introduction of the concept and technique of modern painting has lagged behind. Moreover, oil painting has rich strokes and forms of expression, and is good at expressing charm in an abstract way. This kind of painting art works is quite different from the conventional natural scene images in vision. The traditional oil painting damaged area repair algorithm is too sensitive to black and white color when calculating the pixels in the damaged area, which is prone to color coverage. Therefore, we propose an algorithm design of oil painting damaged area restoration based on convolutional neural network. The convolution neural network is used to repair the damaged oil painting. The restoration process is modeled by the restoration function, and the restoration model is constructed by applying additive noise to the input oil painting image with damaged areas. The core idea of the algorithm is to extract the candidate areas of seals or inscriptions in Chinese painting and calligraphy images by using the prior knowledge of the scene (such as the color and edge of seals and inscriptions). Then, the pre-trained model is used to accurately locate the seal or inscription.","PeriodicalId":124469,"journal":{"name":"2023 Asia-Europe Conference on Electronics, Data Processing and Informatics (ACEDPI)","volume":"459 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125834308","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

Visual Modeling Technology for Computer to Modal Numerical Simulation 计算机到模态数值模拟的可视化建模技术

2023 Asia-Europe Conference on Electronics, Data Processing and Informatics (ACEDPI) Pub Date : 2023-04-01 DOI: 10.1109/ACEDPI58926.2023.00067

Zhenghong Jiang, Chunrong Zhou

引用次数: 0

Optimization Algorithm of Transmission Line Defect Detection and Identification Based on Embedded AI 基于嵌入式AI的输电线路缺陷检测与识别优化算法

2023 Asia-Europe Conference on Electronics, Data Processing and Informatics (ACEDPI) Pub Date : 2023-04-01 DOI: 10.1109/ACEDPI58926.2023.00010

Yi Jiang, Hanghang Zhao, Weixing Li, Ning Wang, Min Fan, H. Wang

引用次数: 0

Design of Color Matching Algorithm for Animation Character Background Based on Decision Tree Classification Model 基于决策树分类模型的动画角色背景颜色匹配算法设计

2023 Asia-Europe Conference on Electronics, Data Processing and Informatics (ACEDPI) Pub Date : 2023-04-01 DOI: 10.1109/ACEDPI58926.2023.00028

Mengyang Kan, Ziyun Liu

{"title":"Design of Color Matching Algorithm for Animation Character Background Based on Decision Tree Classification Model","authors":"Mengyang Kan, Ziyun Liu","doi":"10.1109/ACEDPI58926.2023.00028","DOIUrl":"https://doi.org/10.1109/ACEDPI58926.2023.00028","url":null,"abstract":"The traditional query technology can not solve the problem of information explosion, how to manage it effectively and how to use the data in the database effectively. As a very important visual element in film and television animation, color is not only the first element to stimulate people’s vision, but also the most important means of expression for film and television animation modeling. Classification research develops rapidly in foreign countries, and there are many algorithms and models, but it lags behind in domestic development. Among them, the decision tree method is the most widely used. For managers, the prediction of the decision tree classification model can better and more accurately predict the development trend of animated character backgrounds, and can guide the animation character background managers to make corresponding adjustments. The color in animated movies has always been the recognition of movie characters, the contrast of movie atmosphere, the positioning of movie style, and the influence of movies on audience psychology. Different decision tree algorithms have different characteristics, fully understand the advantages and disadvantages of each algorithm, master its specific application environment, and make it easy for researchers to clarify the improvement points and research direction of the algorithm. It is also easy for users to select and apply. Decision tree algorithms are often applied to large data processing. In the prediction of decision tree classification model, a lot of information needs to be processed, and decision tree algorithm can handle this problem well. It affects the direct feeling of the audience to the work, and whether the color is used properly in the animation creation directly affects the success or failure of the work. This paper mainly makes a decision tree classification model for animated character background color matching algorithm to predict the heat of animated characters.","PeriodicalId":124469,"journal":{"name":"2023 Asia-Europe Conference on Electronics, Data Processing and Informatics (ACEDPI)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134013027","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

Discovering variation financial performance of ESG scoring through big data analytics 通过大数据分析发现ESG评分财务绩效的差异

2023 Asia-Europe Conference on Electronics, Data Processing and Informatics (ACEDPI) Pub Date : 2023-04-01 DOI: 10.1109/ACEDPI58926.2023.00036

Yang Daying, You Zi’Ao

{"title":"Discovering variation financial performance of ESG scoring through big data analytics","authors":"Yang Daying, You Zi’Ao","doi":"10.1109/ACEDPI58926.2023.00036","DOIUrl":"https://doi.org/10.1109/ACEDPI58926.2023.00036","url":null,"abstract":"The newest innovation in the world of corporate reporting is environmental disclosure. In actuality, it is a technique that may more accurately depict a company’s ability to produce financial performance over time. Therefore, utilising the moderating influence of social and ethical behaviours, this article examines whether environmental disclosure (ED) done by companies listed on the ESG index affects their financial performance (FP). Both possibilities and problems for financial innovation are brought by the growth of big data (BD). In many respects, the development of BD has given comfort to individuals and civilizations. Additionally, there is a dearth of empirical research examining the impact of the BD on financial performance and market value. This suggests that although a weak environmental disclosure lowers financial performance, a good one raises it. Additionally, the study contends that social and ethical behaviours have a moderating influence on the relationship between environmental disclosure and the firm’s financial performance. The recently established double machine learning framework may handle interesting causal concerns, whereas the naïve use of machine learning typically fails in this situation. The most recent findings for categorising attitudes using classical classifiers like Naive Bayes and transfer learning models like CNN surpass the Naive Bayes and model classifiers, according to extensive research and tests.","PeriodicalId":124469,"journal":{"name":"2023 Asia-Europe Conference on Electronics, Data Processing and Informatics (ACEDPI)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134492953","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

Elevator Shaft Template System Based on NFC and Cloud Computing Technology 基于NFC和云计算技术的电梯井筒模板系统

2023 Asia-Europe Conference on Electronics, Data Processing and Informatics (ACEDPI) Pub Date : 2023-04-01 DOI: 10.1109/ACEDPI58926.2023.00066

Xiao-Yan Fang

引用次数: 0

Artificial intelligence applied to supermarket intelligent replenishment robot based on machine vision 人工智能应用于基于机器视觉的超市智能补货机器人

2023 Asia-Europe Conference on Electronics, Data Processing and Informatics (ACEDPI) Pub Date : 2023-04-01 DOI: 10.1109/ACEDPI58926.2023.00063

Xuefei Gao

引用次数: 0

Bike-sharing Usage Prediction Based on PCA-GABP Network Model 基于PCA-GABP网络模型的共享单车使用预测

2023 Asia-Europe Conference on Electronics, Data Processing and Informatics (ACEDPI) Pub Date : 2023-04-01 DOI: 10.1109/ACEDPI58926.2023.00041

Guoyu Yin, Jiacheng Xue, Zhikang Lin

{"title":"Bike-sharing Usage Prediction Based on PCA-GABP Network Model","authors":"Guoyu Yin, Jiacheng Xue, Zhikang Lin","doi":"10.1109/ACEDPI58926.2023.00041","DOIUrl":"https://doi.org/10.1109/ACEDPI58926.2023.00041","url":null,"abstract":"The emergence of bike sharing has facilitated our lives, but at the same time, there are problems such as spatiotemporal imbalance. Considering the influence of various natural and human factors on the usage of shared bicycles, this paper selects the data on shared bicycles: in Seoul for a period of time. It combines the principal component analysis method to reduce the comprehensive weights of evaluation indexes. Then, it uses the reduced feature information as the input layer of the GA-BP neural network, which constructs a PCA-GA-BP network model with an accuracy rate of 95%. It conducts a comparison with various other models. The accuracy and practicality of the model were verified by comparing it with various other models. The experimental results show that the usage of shared bicycles is higher during the peak commuting period and midday than during other periods; under the influence of specific special festivals and extreme weather, the usage of shared bicycles is significantly lower. Combined with the experimental results, it can provide scientific and practical guidance for managing and optimizing bike sharing placement and scheduling.","PeriodicalId":124469,"journal":{"name":"2023 Asia-Europe Conference on Electronics, Data Processing and Informatics (ACEDPI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127962201","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