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检索条件"任意字段=3rd IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2024"

共 316 条记录，以下是41-50 订阅

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Research on Network Management System of University Human Resources Based on Computer Platform 3

Research on Network Management System of University Human Re...

引用

3rd ieee international conference on electrical engineering, big data and algorithms, eebda 2024

作者： Wang, Siwei Shanghai University Shanghai China

ISBN: (纸本)9798350380989

This paper analyzes the business process of university personnel information management system. Then, based on the university cloud platform, combined with big data, combined with business services and diversified business services, the university personnel management system was established. Based on Microsoft Biztalk server, this system builds a new type of university human resource management system. Taking Microsoft Biztalk Server as an example, a service mode based on Biztalk server is proposed to solve the problems existing in the current university personnel work. To solve this problem, an optimization method based on genetic algorithm is proposed. On this basis, a new intelligent sorting algorithm is proposed. Compared with the existing algorithm, this algorithm saves 7.261s operation time. The algorithm is implemented on Biztalk server and its validity is verified. By experimental test, compared with the existing algorithms, the proposed optimization method can shorten the inference time. In this study, the optimization method based on genetic algorithm is used to optimize Biztalk server. Experimental results show that the running time of the algorithm is shorter. This has a certain reference significance for the design of Biztalk server. This method can effectively reduce the manual allocation task in the big data environment. The thesis has certain reference significance for promoting the informatization construction of school personnel work. © 2024 ieee.

关键词： big data dynamic programming model dynamic scheduling human resource management network management

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Supplier Management Decision Support System Under data Mining algorithms 3

Supplier Management Decision Support System Under Data Minin...

引用

3rd ieee international conference on electrical engineering, big data and algorithms, eebda 2024

作者： Kun, Chen Zehua, Han Rui'an, Lin Xuejun, Wang Dongdong, Song Fujian Great Power Science and Technology Co. Ltd. Fuzhou Fujian350000 China State Grid Information & Telecommunication Group Co. Ltd. Changping Beijing102200 China

ISBN: (纸本)9798350380989

This article proposed a supplier management decision support system based on data mining algorithms, aiming to help enterprises select the best supplier to improve procurement efficiency and reduce procurement costs. The system used data mining algorithms to analyze and mine the historical data of suppliers. It established a supplier evaluation model and combined it with AHP (Analytic Hierarchy Process) to conduct supplier evaluation. At the same time, the system also used fuzzy comprehensive evaluation method and TOPSIS (Technique for Order Preference by Similarity to ideasolution) method to sort and select suppliers. The experimental results indicated that the system could quickly and accurately evaluate suppliers, and improve procurement efficiency and reduce procurement costs, which has practical application value. This article also discussed and prospects the research, and proposed future research directions. © 2024 ieee.

关键词： Analytic Hierarchy Process data mining Algorithm Decision Support System Fuzzy Comprehensive Evaluation Method Supplier Management TOPSIS Method

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A Study of Multibeam Line Bathymetry Problems Combined with Digital Visualization Techniques 3

A Study of Multibeam Line Bathymetry Problems Combined with ...

引用

3rd ieee international conference on electrical engineering, big data and algorithms, eebda 2024

作者： Li, Jinze Dongbei University of Finance and Economics Dalian China

ISBN: (纸本)9798350380989

In this paper, we address the problem of multibeam bathymetry to establish the optimal survey line layout for seafloor bathymetry by using geometric relationships in different situations, combining optimization algorithms and nonlinear planning models as well as data fitting and data visualization. First, a mathematical model of the coverage width of multibeam bathymetry and the overlap rate between adjacent strips is established. Then, the mathematical model of the coverage width of multibeam bathymetry is established in the case where there is an angle between the direction of the survey line and the projection of the normal direction of the seafloor slope on the horizontal plane. Again, a set of survey lines with the shortest measurement length that meets the requirements is designed, and the problem is transformed into a constrained optimization problem, which is solved based on the nonlinear programming method under the given constraints. Finally, the bathymetric data of a given sea area, given the relevant constraints, find the total length of the survey lines, and formulate an optimization strategy to achieve minimizing the total length of the survey lines and maintaining sufficient coverage and controlling the overlap rate, to find the optimal layout of the survey lines to satisfy the survey task. The proposed model is easy to understand, capable of handling complex constraints, and very flexible in practical problems. © 2024 ieee.

关键词： data Fitting Digital Visualization Geometric Relations Nonlinear Programming Optimization algorithms

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Detection and Analysis of Thermal Runaway Acoustic Signal Characteristics of Energy Storage Lithium Battery 3

Detection and Analysis of Thermal Runaway Acoustic Signal Ch...

引用

3rd ieee international conference on electrical engineering, big data and algorithms, eebda 2024

作者： Xu, Song Wan, Tao Wu, Junjie Zha, Fanglin Cai, Yufeng Liu, Yiyi State Grid Hunan Electrical Power Company Limited Research Institute Changsha China

ISBN: (纸本)9798350380989

Acoustic signal is commonly generated in the thermal runaway process of lithium energy storage batteries. In order to understand the acoustic information of the lithium batteries, an experimental platform is designed to test the thermal runaway sound signals of different type of lithium blade batteries. The sound variance process of thermal runaway is recorded. Time-and-frequency-domain methods are used to analyze the acoustic characteristics of the batteries. It is found that thermal runaway can be detected with sound test method. The research result validates that acoustic method could be used as a new technology for early and ultra-early safety warning of lithium batteries, which is of great significance to the safe operation of energy storage stations. © 2024 ieee.

关键词： acoustic signal lithium battery safety warning thermal runaway

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Life Expectancy Prediction Based on Particle Swarm Optimization Support Vector Machine Regression 3

Life Expectancy Prediction Based on Particle Swarm Optimizat...

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3rd ieee international conference on electrical engineering, big data and algorithms, eebda 2024

作者： Guo, Zhaodong Que, Yuanxi Li, Xiang College of Artificial Intelligence and Data Science Hebei University of Technology Tianjin China College of Computer Science & Software Engineering Shenzhen University Shenzhen China College of Computer Science Nankai University Tianjin China

ISBN: (纸本)9798350380989

This study delves into the application of Particle Swarm Optimization (PSO) algorithms in the parameter optimization of Support Vector Regression (SVR) models to enhance the accuracy of predicted average life expectancy. An adaptive PSO algorithm augmented with random perturbations is introduced. Through a fitness-function-guided dynamic adjustment mechanism, this method circumvents the premature convergence issue typical of conventional PSO, locating the optimal penalty parameter C and kernel parameter for the SVR model. These parameters are then incorporated into the SVR model for training and regression prediction, achieving optimal data fitting and generalization effects. Comparative analysis reveals that the PSO-enhanced SVR model outperforms the traditional SVR across various performance metrics. Notably, there is a marked improvement in the coefficient of determination, a significant re-duction in root mean square error, and mean absolute percentage error, affirming the advancements of the improved PSO-SVR model in prediction accuracy and reliability. © 2024 ieee.

关键词： Composite Model PSO PSO-SVR SVM

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Research on 3D Model Construction Method Based on Geographic Information System 3

Research on 3D Model Construction Method Based on Geographic...

引用

3rd ieee international conference on electrical engineering, big data and algorithms, eebda 2024

作者： Zhou, Xin Hu, Censi Hubei University of Technology Hbut Wuhan China

ISBN: (纸本)9798350380989

How to establish large-scale 3D GIS efficiently and accurately has become a key issue restricting the development of urban 3D GIS. A large-scale 3D modeling algorithm for abstract objects such as abstract points, lines and surfaces is studied based on the analysis of the principle of terrain modeling in 3D GIS. The software can create various types of 3D models, display and browse, query spatial properties, interoperate, measure and analyze them. The software can not only conduct 3D modeling under the ground, but also overcome the problems that the existing 3D modeling methods can only display but cannot query, measure and edit. The model has the advantages of simple operation, fast operation and automation. It is of great significance in the modeling of terrain, such as ground, river, road, green space, regular building, underground pipeline, etc. Taking the rapid modeling technique described above as an example, the effectiveness of the proposed algorithm is proved. © 2024 ieee.

关键词： City three-dimensional geographic information system symbol matching three-dimensional model triangulation

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Analysis and Research on Python-Based Identification of Abnormal Commodities on E-Tailing Platforms 3

Analysis and Research on Python-Based Identification of Abno...

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3rd ieee international conference on electrical engineering, big data and algorithms, eebda 2024

作者： Tian, Ziye Yan, Ming Ma, Xiaoju Duan, Naixia Wang, Xuecheng School of Information Engineering Shaanxi Institute of International Trade & Commerce Shaanxi Xi'an712000 China Singapore

ISBN: (纸本)9798350380989

With the rapid development of e-commerce, e-tailing platforms have become the main way for people to shop, but e-tailing platforms are also facing some problems, such as untrue information of commodities, false price labeling, and brushing behavior. This paper analyzes and researches the anomaly identification method of e-commerce goods online retail platform. Based on the relevant commodity data and store data information provided by so-and-so big data industry company, the paper firstly adopts exploratory data analysis method, analyzes the characteristics of the data, and draws out the characteristics and causes of abnormal data. Then an anomaly detection method is proposed based on the characteristics of e-commerce goods. This method includes three steps: dimensional organization, extreme anomaly data detection and suspicious data detection, and fully applies machine learning algorithms such as isolated forests to realize the anomaly detection of e-commerce commodity data. Finally, we use the relevant data information provided by So-and-so big data Co. Ltd. to verify the effectiveness of the e-commerce commodity (price, sales volume) e-tailing platform anomaly identification method proposed in this paper, and the experimental results show that this system has a high accuracy rate and efficiency. © 2024 ieee.

关键词： anomaly monitoring data analysis isolated forest machine learning

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Design and Implementation of Marketing Classification System Based on Artificial Intelligence 3

Design and Implementation of Marketing Classification System...

引用

3rd ieee international conference on electrical engineering, big data and algorithms, eebda 2024

作者： Tian, Shuo Shanghai University Shanghai China

ISBN: (纸本)9798350380989

This paper mainly introduces some machine learning methods used in the field of data mining. The method of data mining is discussed by taking market segmentation algorithm as an example. This paper presents an improved support vector machine method. By judging the similarity between each sampling point and its closest class, the classifier is obtained by training it with support vector machine. A method based on stepwise approximation method is proposed to solve the problem of too large size of KNN training samples. The experimental results show that non-SVM is superior to SVM in classification accuracy and classification speed. In addition, this project will also adopt artificial intelligence technology to build a data analysis system for high-end wine, analyze, compare and match massive information data of high-end wine through data mining, and discover the comparison information and market potential of main ingredients in high-end wine. It is compared with the chemical composition of high-grade red wine, and the relevant marketing treatment of high-grade red wine is obtained. It can help high-grade red wine manufacturers to analyze the composition content and quality of high-grade red wine. © 2024 ieee.

关键词： artificial intelligence data analysis data mining high-end red wine Machine learning marketing classification algorithm

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Design of On-Board data Download and Application Platform of EMU Based on 5G 3

Design of On-Board Data Download and Application Platform of...

引用

3rd ieee international conference on electrical engineering, big data and algorithms, eebda 2024

作者： Yang, Chunhui Zhang, Weijiao Cheng, Kai Li, Chaoxu Institute of Computing Technologies China Academy of Railway Sciences Corporation Limited Beijing100081 China

ISBN: (纸本)9798350380989

The on-board data of EMU is the parameter information collected by the sensor during the operation of EMU, which plays an important role in evaluating the operating state of EMU and analyzing the cause of fault in depth. By analyzing the situation of vehicle data and combining the characteristics of 5G technology, this paper puts forward a method of vehicle data download based on 5G, designs an EMU vehicle data download and application platform, and adopts key technologies such as massive data processing and monitoring, batch efficient data analysis and large amount of data storage. To achieve vehicle data collection and transmission, data monitoring, data analysis, data sharing and comprehensive display and other functions. The realization of the platform is helpful to further promote the application of on-board data of EMU, which is of great significance to promote the fault analysis of EMU and the application of state evaluation and prediction. © 2024 ieee.

关键词： big data processing data parsing EMU integrity checking On-board data

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Large-scale data Mining algorithms and Models for Equipment and Power Supply Service Information Fusion 3

Large-scale Data Mining Algorithms and Models for Equipment ...

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3rd ieee international conference on electrical engineering, big data and algorithms, eebda 2024

作者： Xiang, Chen Zhaozhi, Zhang Yi, Xie Zhong, Zheng Weiqi, Lin State Grid Fujian Marketing Service Center Metering Center and Integrated Capital Center Fujian Fuzhou350001 China State Grid Fujian Electric Power Company Co. Ltd. Fuzhou350001 China Fujian Power Supply Service Co. Ltd. Fuzhou350001 China State Grid Info-Telecom Great Power Science and Technology Co. Ltd. Fuzhou350003 China

ISBN: (纸本)9798350380989

With the rapid development of computer technology, the requirements for power quality of power systems are becoming more and more stringent. This article aims to study key issues in the integration of information resources for power supply services. First, this article provides an analysis of current device and communications data sources and their characteristics. Secondly, this article introduces feature selection data mining methods such as multi-user multipath ensemble algorithm, model-based feature extraction strategy and heuristic matching strategy based on task environment. Finally, this article uses Matlab for verification and obtains experimental results. The accuracy of this algorithm is at least 90% and can reach as high as 99%;the memory usage of the model is within 0.06;the stability of the model is between 0.8-0.89. © 2024 ieee.

关键词： data Mining Information Fusion Power Supply Model Power Supply Service

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