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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31-40 订阅

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Research on Sports Competition Record System Based on Computer big data Technology 3

Research on Sports Competition Record System Based on Comput...

引用

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

作者： Chunlan, Fan Zelong, Shao Physical Culture Institute Sichuan University of Arts and Sciences Sichuan Province Dazhou China Physical Culture Institute Southwest Medical University Sichuan Province Luzhou City China

ISBN: (纸本)9798350380989

This paper takes NET as the development tool and uses C++ programming to realize the program of basketball game time scoring subsystem based on Windows. The data collected by the basketball game recording system is analyzed by using SQL statement, and the useful technical and tactical information is output to the user. The modular structure ensures that the system can ensure the completeness and consistency of data in information retrieval. This system includes player information entry, foul information record and statistics, player substitution, score record, game time, 24-second countdown, game time and score. The Apriori method is used to find the strategies related to basketball games, and the relevant rules of basketball strategy arrangement are constructed accordingly. It is found that the basketball technology and tactical analysis software of Apriori algorithm developed by NET technology can effectively filter non-game images. This lays a foundation for the study of basketball tactics. © 2024 ieee.

关键词： design and research NET platform recording system

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Fault Analysis Method for Distribution Network Operation and Maintenance Based on Improved Random Forest Algorithm 3

Fault Analysis Method for Distribution Network Operation and...

引用

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

作者： Nie, Ding Fan, Litao Bi, Yunchuan Yunnan Power Grid Co. Ltd. Electric Power Science Research Institute Yunnan Kunming China

ISBN: (纸本)9798350380989

In order to improve the quality and efficiency of the distribution network emergency repair failure quantity, this paper proposes an improved random forest algorithm to evaluate the distribution network emergency repair failure quantity. A distribution network emergency repair failure system is designed, including the monitoring master station, the communication module and the fault location monitoring module. The three parts use fault location monitoring technology to realize rapid repair of Distribution network faults through data communication and processing, and use an improved random forest algorithm to evaluate the amount of emergency repairs of distribution network faults. Experiments show that the evaluation accuracy of the system's emergency repair failure volume studied in this paper fluctuates around 90%, the maximal value reaches 97%, which improves the evaluation capability of the distribution network emergency repair failure volume. © 2024 ieee.

关键词： big data emergency repair of distribution network fault quantity evaluation location monitoring random forest

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Research on Sports Competition Result Prediction System Based on Computer big data Machine Learning Model 3

Research on Sports Competition Result Prediction System Base...

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

作者： Lu, Xiaolong Li, Ming Ye, Chao Yunnan Vocational College of Sports Yunnan Kunming China Yunnan Youth Sports Training Center Yunnan Kunming China

ISBN: (纸本)9798350380989

Using big data theory to analyze athletes' performance data, this paper finds out the changing characteristics of athletes' performance. Using the principle of big data, we find the performance characteristics of athletes in the training process. The particle swarm optimization (PSO) method is used to predict the network parameters of support vector machine (SVM) online. The validity of this method is verified by testing on college students. This method can track athletes' performance characteristics more accurately, so as to build an excellent sports performance prediction model. The model can detect future trends from athletes' performance data in data mining and machine learning. This kind of system has a wide application prospect, and can greatly improve the efficiency and quality. The method combines machine learning theory with support vector machine network, which can effectively improve the prediction accuracy. This method has a very broad application prospect. © 2024 ieee.

关键词： Athlete performance changing situation machine learning model prediction model

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data Analysis of Cross-Border E-Commerce Entrepreneurship Based on User Portraits 3

Data Analysis of Cross-Border E-Commerce Entrepreneurship Ba...

引用

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

作者： Li, Long Nanning College for Vocational Technology Nanning Guangxi China

ISBN: (纸本)9798350380989

This paper proposes a transnational e-commerce platform based on user portrait. The system adopts Spring Mvc+ spring+ mybatis architecture. Using MySQL5.7 database, Tomcat7.0 server, redis cache and other methods, customers and merchants are seamlessly connected to provide prototypes. A method based on 'word frequency-text frequency-tag weight' is proposed to model business records of a large number of customers in cross-border e-commerce enterprises. This project establishes a personalized marking system based on customer portraits to conduct in-depth research on the customer service activities of multinational e-commerce enterprises. We tap into the hidden high-risk information and present it to consumers. Practice has proved that dangerous behaviors can be found effectively by modeling user characteristics in the network, which help cross-border e-commerce to achieve data security operation dynamic monitoring. Based on word frequency statistics, the algorithm based on word frequency and PDF is convenient for statistics and calculation, and it is used to calculate the E-mail text frequency. In the project, we propose a clustering algorithm based on user behavior, which can extract user interest model from raw data. Through the analysis of user behavior, we can better understand the user's behavior pattern. And through the understanding of users, we discover the potential needs of users, which can provide valuable services for enterprises. © 2024 ieee.

关键词： Cross-border e-commerce entrepreneurial analysis user portrait word frequency-inverse document algorithm

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Design of Marketing Analysis System Based on data Mining Technology 3

Design of Marketing Analysis System Based on Data Mining Tec...

引用

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

作者： Fu, Jie Shanghai University Shanghai China

ISBN: (纸本)9798350380989

This paper designs a power marketing data analysis system based on data mining technology. Then the software and hardware of the scheme are optimized respectively. The main contents of this paper include: data collection, data mining and data processing. Then a new multi-level clustering method based on implicit Markov pattern is proposed. The method converts the time series of a time series into a likelihood space in which the likelihood value is identified by a symmetric KL distance. A symmetric KL migration matrix is constructed, and the access modes of users are divided into different levels by the idea of hierarchical clustering. Then a complete power grid enterprise information system is established, which is an important part of the power grid marketing system. Online analysis technology is used to ensure the whole logic input, so as to ensure the normal operation of the power marketing management system. The experiment shows that this method can realize the comprehensive processing of all kinds of electricity information, and will not cause large fluctuations. © 2024 ieee.

关键词： data analysis data integration data mining electric power marketing hidden markov model

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Research on POI data System for External Breakdown Prediction of Distribution Network Based on Computer Genetic Algorithm 3

Research on POI Data System for External Breakdown Predictio...

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

作者： Qian, Yuzhou Lin, Wenyu Ye, Xuehui Li, Weiming Zhong, Jiangteng Shen, Haoyu State Grid Zhejiang Electric Power Co. Ltd. Ningbo Yinzhou District Power Supply Company Ningbo China

ISBN: (纸本)9798350380989

In this paper, an external fault location method of kernel POI data system is proposed. First, auxiliary operators are used to increase the likelihood of individuals in the group. The genotype is both male and female. This method greatly improves the optimization performance of this method. Then, an optimization method based on hierarchical process is proposed. First, the distribution network is partitioned. It is divided into multiple trunk lines and multiple partitions that are isolated from each other. Then this method is applied to determine the fault point of each individual partition. This algorithm reduce the size of the problem and speed up the search. Computer simulation method is feasible for the multi-point faults in distribution networks with distributed power supply. The results show the conventional genetic algorithm in stability and accuracy. © 2024 ieee.

关键词： Distribution Network Fault Location Fitness Genetic Algorithm Hierarchical Treatment Outbreak Prediction

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A Study of the Advantages of Clustering and Gray Prediction algorithms for the Prediction of data Metrics 3

A Study of the Advantages of Clustering and Gray Prediction ...

引用

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

作者： Yang, Songpu Li, Kangli Shenyang Aerospace University Shenyang China

ISBN: (纸本)9798350380989

In this paper, the clustering algorithm is used for the contraction city classification algorithm. First of all, the big data are dimensionless, and by analyzing the growth rate of each factor, the cities are divided into five categories according to the contraction characteristics of each factor. Through the gray correlation analysis, the weights of different factors affecting the contraction of the city are ranked, and the gray correlation can better solve the problem of uncertainty of influencing factors between multiple indicators, and can supplement the defects of the traditional model. Finally, the gray prediction method is used to predict the future development trend. Compared with the traditional prediction model, the gray prediction model requires less data volume, and only a small amount of incomplete information is needed for model building and prediction. Gray system theory is able to deal with poor information systems, with lower requirements on the smoothness of data, and with a wider scope of application. The gray prediction model adopts gray mathematics to deal with uncertainty, which can make the urban development prediction results closer to reality and improve the prediction accuracy. Finally, curve fitting is used to get the development trend of urban shrinkage. © 2024 ieee.

关键词： Curve fitting Entropy method Gray correlation analysis Gray predictive model K-means++

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A Study on the Pricing of Used Sailboats: Utilizing Random Forest Models to Analyze the Impact of Multiple Factors 3

A Study on the Pricing of Used Sailboats: Utilizing Random F...

引用

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

作者： Zhou, Huimin Qian, Jiajun Sun, Feifan School of Mathematics and Big Data Chongqing University of Arts and Sciences Chongqing China Suzhou University of Science and Technology Faculty of Electronic and Information Engineering Suzhou China College of Economics and Management Northeast Forestry University Harbin China

ISBN: (纸本)9798350380989

This study explores the impact of various factors on the valuation of sailboats. The research delves into the mathematical correlation between the prices of secondhand sailboats and 11 specific factors. Initially, any missing values were removed, outliers were substituted, and box plots were utilized to validate the precision of the sample data. Furthermore, five supplementary parameters were sourced from public websites, encompassing displacement, draft, beam, material, and GDP. Subsequently, after organizing the data, categorical variables were encoded using sequence and label encoding. Following this, multiple linear regression models, ridge regression models, and random forest models were constructed using the entire dataset. Through a comparative analysis of the three models' accuracy, the random forest model was chosen as the ultimate model for elucidating the pricing of each sailboat. The predictive precision of the random forest model was scrutinized, yielding a prediction accuracy of R2=0.786. © 2024 ieee.

关键词： Mathematical relationship Multiple linear regression models Random forest model Sailboats

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A Detection Method for Typical Component of Space Aircraft Based on YOLOv3 Algorithm 3

A Detection Method for Typical Component of Space Aircraft B...

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

作者： He, Bian Jianzhong, Cao Cheng, Li Junpeng, Dong Zhongling, Ruan Chao, Mei Xi'an Institute of Optics and Precision Mechanics of Cas Xi'an China University of Chinese Academy of Sciences Beijing China Xi'an Key Laboratory of Spacecraft Optical Imaging and Measurement Technology Xi'an China

ISBN: (纸本)9798350380989

A solar panel recognition method based on YOLOv3 deep learning algorithm is proposed to address issues such as inaccurate recognition of traditional algorithms in space solar panel detection. First, this paper scales the dataset images to 416 × 416, then uses Labelme to annotate the data and transform the bounding box position information, and finally uses the YOLOv3 algorithm framework for model training. The results show that the recall, F1 score and accuracy of YOLOv3 algorithm are all above 80%. The YOLOv3 deep learning algorithm meets the requirements for real-time detection of solar panels in terms of accuracy. © 2024 ieee.

关键词： Deep learning object detection Space debris YOLOv3

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Research on data Platform Construction and Security of Information Network Based on Blockchain Technology 3

Research on Data Platform Construction and Security of Infor...

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

作者： Zhou, Yue Gao, Tianfang Feng, Qianlong Zhang, Fan China Automotive Technology and Research Center Co. Ltd. Tianjin China Co. Ltd. Tianjin China

ISBN: (纸本)9798350380989

The idea of blockchain is introduced, and the security of computer network is studied. Its main goal is to enhance the confidentiality and privacy of the data transfer and sharing process in the network. This project intends to convert the generated contract into a network-based expression of block coding and block information fusion, and combine this information expression with the security of computer networks to form an information security intelligent contract. This paper presents the process of identity authentication in network-based information system. Demand aggregation and buffering are used to reduce the amount of redundant communication in the network and speed up the transmission of communication. The use of off-chain storage can not only reduce the storage burden on the blockchain, but also ensure the safety and security of the data. The experimental simulation verifies that the trust distribution method based on blockchain and attribute can effectively control the access to data, and provide users with more secure and reliable information sharing and publishing services. © 2024 ieee.

关键词： blockchain data distribution data encryption network data security sharing technology

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