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4th International Conference on Applied Mathematics, Modeling and Computer Simulation, AMMCS 2024

作者： Li, Jing Xu, Yanan Department of Artificial Intelligence Shandong University of Engineering and Vocational Technology China

ISBN: (纸本)9781643685519

In order to implement the training plan for on-site engineers in the field of big data technology in higher vocational education. With the development of artificial intelligence technology, big data technology, cloud computing technology, etc., exploring the construction of digital resources for big data technology majors is helpful for the training of on-site engineers. The article takes the construction of artificial intelligence courses as an example to explore the construction and application strategies of digital teaching resources for big data technology majors. This article mainly elaborates on the development of a talent training plan for big data technology majors under the OBE framework, combined with the ADDIE model to optimize the development and implementation of digital resources. Through digital resource platforms, a new model of personalized talent cultivation can be achieved, the teaching process can be optimized, teaching and learning outcomes can be improved, and educational evaluation methods can also be enriched. © 2024 The Authors.

关键词： ADDIE course construction big data technology Digital teaching resources

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Research on performance evaluation of intelligent manufacturing enterprises supported by machine learning and big data technology

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING technology 2024年第5-6期130卷 2811-2832页

作者： Zhang, Bangjin Guangzhou Coll Commerce Sch Accounting Guangzhou 511363 Peoples R China

Intelligent manufacturing, as a pillar of the manufacturing industry, provides crucial support for achieving China's strategic goal of becoming a manufacturing powerhouse. The operation and management process of intelligent manufacturing enterprises requires a large amount of capital investment, and the efficiency of capital utilization directly affects the economic benefits of intelligent manufacturing enterprises. Relevant enterprises continue to improve the performance evaluation mechanism and enhance their performance evaluation ability, so as to effectively promote the realization of corporate strategic objectives and continue to become a solid support for the steady operation of China's economy. On this basis, the performance of intelligent manufacturing enterprises was deeply explored, and a set of performance evaluation indicator framework for intelligent manufacturing enterprises was established by using machine learning and big data technology. Through empirical analysis, machine learning methods are introduced into performance evaluation to establish an assessment mechanism for intelligent manufacturing enterprises that is suitable for China's national conditions. For ridge regression, lasso regression, and elastic network regression in machine algorithm, we have conducted in-depth research and built a set of performance evaluation system using the model of lightGBM. Construct a framework of performance evaluation system for intelligent manufacturing enterprises based on machine learning and big data technology support, and use TOPSIS method to conduct empirical analysis, thus further highlighting the importance of evaluation and feedback mechanism for intelligent manufacturing enterprises.

关键词： Machine learning big data technology Intelligent manufacturing Performance evaluation

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Application of big data technology in enterprise information security management

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SCIENTIFIC REPORTS 2025年第1期15卷 1-15页

作者： Li, Ping Zhang, Limin Hunan Int Econ Univ Sch Informat & Mechatron Engn Changsha 410205 Peoples R China Hunan Inst Traff Engn Coll Elect & Informat Engn Hengyang 421001 Hunan Peoples R China

This study aims to explore the application value of big data technology (BDT) in enterprise information security (EIS). Its goal is to develop a risk prediction model based on big data analysis to enhance the information security protection capability of enterprises. A big data analysis system that can monitor and intelligently identify potential security risks in real-time is constructed by designing complex network analysis algorithms and machine learning models. For different types of security threats, the system uses feature engineering and model training processes to extract key risk indicators and optimize model prediction performance. The experimental results show that the constructed risk prediction model has excellent performance on the test set, and its Area Under the Curve reaches 0.95, indicating that the model has good differentiation ability and high prediction accuracy. In addition, in the multi-class risk identification task, the model achieves an average precision of 0.87. Compared with the traditional method, it has remarkably improved the early warning accuracy and response speed of enterprises to various information security incidents. Therefore, this study confirms the effectiveness and feasibility of applying BDT to EIS risk management, and the successfully constructed prediction model provides strong technical support for EIS protection.

关键词： big data technology Enterprise information security Risk prediction model Information security

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An international value chain of China's manufacturing industry based on big data technology

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JOURNAL OF CONTROL AND DECISION 2025年第2期12卷 195-208页

作者： Liu, Ning Shen, Zhifeng Zang, Jianglong Li, Xialing Jiangsu Univ Technol Changzhou Peoples R China Heller Machinery Changzhou Co Ltd Changzhou Jiangsu Peoples R China

In order to study the impact of the vertical specialisation level and competitiveness of China's manufacturing industry on the international competitiveness of the manufacturing industry, this paper combines improved data mining technology to analyze the rising factors of the international value chain of the manufacturing industry and construct a regression equation. Moreover, this paper analyzes the impact of vertical specialisation on the competitiveness of manufacturing industry by adding control variables, and finally puts forward policy recommendations for improving the international competitiveness of manufacturing based on the results of empirical analysis, thereby promoting the rise of the status of China's manufacturing industry in the division of labour in the international value chain. The research shows that the analysis model of rising factors of manufacturing international value based on big data technology proposed in this paper has good results.

关键词： big data technology manufacturing international value chain rising factors

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Analysis of factors influencing Chinese vocabulary learning level based on big data technology

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2024年第2期46卷 3545-3556页

作者： Li, Yajie Cai, Xirui Huashang Coll Guangzhou Guangdong Peoples R China Kunming Med Univ Dept Foreign Languages Kunming 650500 Yunnan Peoples R China

In recent years, significant progress has been made in the study of Chinese vocabulary acquisition, and the research content and scope have gradually expanded. Chinese vocabulary is the foundation for understanding and using language, and any language has developed on the basis of Chinese vocabulary. Many studies have shown that there are many factors that affect the acquisition of Chinese vocabulary, and the impact on Chinese vocabulary acquisition is also different. Among them, the influencing factors of Chinese vocabulary acquisition have gradually become a research hotspot, and a large number of related empirical studies have emerged. Based on the big data technology and the random effect model, this paper comprehensively analyzes whether the influencing factors of Chinese vocabulary acquisition as a second language are significant and investigates the effects of internal and external influencing factors, delayed post-test, specific factors and experimental interval time on the learning effect. External factors significantly impact Chinese vocabulary acquisition, including learning style, input factors and input methods. Through the subgroup analysis of the experimental interval, we find that the effect of Chinese vocabulary acquisition decreases with the extension of the experimental interval. Therefore, this paper holds an inverse relationship between the experimental interval and the development of Chinese vocabulary acquisition.

关键词： Chinese second language Chinese vocabulary big data technology analysis of influencing factors

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Computer big data technology in additive manufacturing and product design in sustainable manufacturing

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING technology 2024年第9-10期135卷 4855-4863页

作者： Ding, Caichang Li, Chao Xiong, Zenggang Li, Zhimin Hubei Engn Univ Sch Comp & Informat Sci Xiaogan 432000 Peoples R China Hubei Univ Technol Sch Comp Sci Wuhan 430068 Peoples R China

The efficiency of remanufacturing systems is closely related to the modular design. This paper proposes a sustainable design concept aiming at active remanufacturing. This paper adopts the modular method related to parameter flow to decompose and construct the product's function. The author applies the clustering method to the parameter flow correlation determination to realize the quantitative division of modules. This paper combines sustainable design principles with the life cycle characteristics of products. In this paper, the sustainable design is divided into modules based on the degree of component association. Finally, this paper uses an example to demonstrate that the model in this paper can divide products into modules in a sustainable way.

关键词： Computer technology big data technology Sustainable production Product module design Auxiliary production

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big data technology in the Set of Methods and Means of Scientific Research in Modern Scientometrics

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SCIENTIFIC AND TECHNICAL INFORMATION PROCESSING 2022年第2期49卷 102-107页

作者： Melnikova, E., V Russian Acad Sci All Russian Inst Sci & Tech Informat Moscow Russia

The problems of applying big data technology in modern scientometric analysis are considered. The importance and relevance of these problems are determined by the ability of big data to significantly increase the efficiency of scientometric research through in-depth analysis of mega-volumes of heterogeneous data and to identify on this basis new semantic relationships and patterns. The main content of big data technology is disclosed. The article presents a list of data requirements that allow data to be classified as big data;the importance of this technology as the advanced means of scientific research in scientometrics is noted;detailed characteristics of methods of scientific research are given. The features of bibliometric, altmetric, webometric, and probabilistic-statistical methods are analyzed. The important place of big data technology in the modern set of methods and means of scientific research in scientometrics is emphasized.

关键词： big data big data technology scientometrics webometrics cybermetrics scientometric indicators methods of scientific research unstructured data

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Group computing task assignment and association analysis based on big data technology

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INTERNATIONAL JOURNAL OF GRID AND UTILITY COMPUTING 2024年第3-4期15卷 263-272页

作者： Ting, Chen Xian Siyuan Univ Coll Elect Informat Engn Xian Shaanxi Peoples R China

The explosion of data scale makes data processing encounter many difficulties and challenges. The purpose of this paper is to discuss the group computing task assignment and correlation analysis of big data technology. This paper designs and proposes an algorithm for task assignment in big data sets, which is based on the user's exact perception of a topic and aims to improve the accuracy of calculation. This algorithm is first able to effectively combine the topic accurate perception and extraction model with adaptive fuzzy clustering, and then it can be done by building a model that focuses on specific target groups and users, and calculating the degree between them. The experimental results of this paper show that the accuracy of the music dataset is relatively low, averaging 50%;for the compilation of thematic data sets, the accuracy rate is high, averaging 70%;the final task assignment accuracy reaches 79.9%.

关键词： big data technology group computing task assignment association analysis self-processing algorithm

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Application of big data technology in emergency management platform informatization construction

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OPEN COMPUTER SCIENCE 2024年第1期14卷

作者： Lin, Meirong Hainan Vocat Univ Sci & Technol Coll Informat Engn Haikou 571126 Hainan Peoples R China

The emergence of emergencies has impacted China's politics, economy, and other aspects to varying degrees, seriously threatening social stability, economic development, and people's happiness. The emergency management platform plays an important role in the handling of emergencies. The establishment of the emergency management platform can help leaders make correct decisions and reduce the impact of emergencies on the safety of people's lives and property. However, some problems are gradually exposed in the process of establishing the emergency management platform. How to make it play its role better has become an important goal of platform informatization. With the advent of the big data era, big data technology has become a new way of information construction of emergency management platforms. This article mainly discussed the information construction of the emergency management platform. This article proposed to use big data technology to carry out the information construction of the emergency management platform and use the time series data mining algorithm based on the Artificial Neural Network to achieve the prediction function of the platform. The experimental results in this article showed that the prediction rate was 98.0% when the emergencies of the input platform were 50 and 99.0% when the emergencies of the input platform were 300. It can be seen that the emergency management platform designed in this article has a high ability to predict emergencies, so that emergency management measures can be taken in advance to reduce the occurrence of emergencies.

关键词： big data technology artificial neural network emergency management platform information construction time series

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Analysis of the feasibility and advantages of using big data technology for English translation

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SOFT COMPUTING 2023年第16期27卷 11755-11766页

作者： Hu, Jing Nanchang Jiaotong Inst Nanchang 330100 Jiangxi Peoples R China

With the rapid development of science and technology and big data, traditional translation has been greatly tested in the era of big data. The translation ability requires to be endowed with excellent bilingual teaching language ability, rich and diverse translation professional knowledge, sufficient basic translation knowledge, skilled IT technology and computer knowledge, etc., to better shape the translation ability. Based on big data technology, this paper analyzes the feasibility and advantages of using big data technology for English translation by designing a public automatic English translation system and studying the teaching mode of the English translation.

关键词： big data technology English translation Teaching mode Internet data

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