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5th International Conference on Big Data and Security (ICBDS)

作者： Yu'e, Liu Yunnan Univ Dianchi Coll Kunming 650228 Yunnan Peoples R China

ISBN: (纸本)9789819743896;9789819743902

In the current era of big data, the landscape of online public opinion has undergone significant transformations in terms of data volume, complexity, and the speed at which it is generated. The ubiquitous nature of the Internet has bestowed upon online public opinion distinct characteristics: real-time information dissemination, a universal audience reach, transcendence of time and space constraints, and a rapid spread. Internet public opinion (IPO), as a digital mirror of real-world public sentiment, exhibits unique traits that facilitate the swift propagation of public opinion events. This paper delves into these phenomena, focusing on an advanced analytical approach to understanding and managing online public opinion. The core contribution of this research is the development of an improved Birch grey clustering algorithm, which is an enhancement of the existing grey clustering techniques. This improved algorithm is deeply analyzed and combined with the MapReduce framework, a pivotal technology in big data processing. This integration aims to enable parallel grey clustering of online public opinion texts, a methodological innovation in the field of data analysis. The study's findings suggest that this parallel grey clustering approach significantly outperforms traditional grey clustering methods, particularly in terms of efficiency and effectiveness. This superiority is especially pronounced when dealing with the massive volumes of data typically associated with online public opinion. By efficiently categorizing online public opinion texts, this advanced approach lays a strong foundation for more in-depth analyses. It facilitates trend prediction, topic discovery, and the monitoring and tracking of hot spots in online discussions. Such capabilities are increasingly vital in a world where public opinion can rapidly shift and evolve, often with significant implications for social, political, and economic realms. Additionally, the paper presents simulation results th

关键词： grey clustering algorithm Big data Internet public opinion Evolutionary model

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Mental Health Intelligent Evaluation System based on grey clustering algorithm 11th

Mental Health Intelligent Evaluation System based on Grey Cl...

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11th International Conference on Applications and Techniques in Cyber Intelligence, ATCI 2023

作者： Li, Di College of Physical Education Bohai University Jinzhou China

grey theory studies complex systems characterized by "lack of information" and "poor data" with known insufficient information. By deeply mining hidden information from existing data, it obtains data information that is not reflected on the surface, thus achieving targeted historical evaluation and simulation prediction of grey systems. In recent years, various social events have occurred frequently due to the mental health problems of college students, which has attracted widespread attention from public opinion. This article uses the literature research method to construct an analysis and evaluation index system for college students' mental health, determines the grey whitening weight function, and based on the grey clustering algorithm mathematical model, conducts clustering analysis on expert scoring data to study the production laws hidden behind the data, providing new ideas and methods for the research of college students' mental health problems, helping college students overcome psychological problems, and improve the mental health level of college *** has found that the indicators of 'Emotional stability' and 'Social adaptability' are at a high level of mental health issues. © 2024 The Authors. Published by Elsevier B.V.

关键词： Analysis And Evaluation grey clustering algorithm Mathematical Model Mental Health Whitening Weight Function

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Application of Magnetic Resin based on grey clustering algorithm in Advanced Treatment of Industrial Wastewater 2

Application of Magnetic Resin based on Grey Clustering Algor...

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2nd International Conference on Smart Technologies for Smart Nation, SmartTechCon 2023

作者： Mustare, Narendra B. Suguna, R. Saritha, P.S. Abraham, Arockia Raj Jain, Sanjiv Kumar Raja, Ch. Department of Electronics and Instrumentation Engineering CVR College Of Engineering Hyderabad India Department of CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai India Dhanalakshmi Srinivasan College Of Engineering Navakkarai Post Coimbatore India Department of CSE- Data Science Madanapalle Institute of Technology and Science Madanapalle Chittoor India Department of Electrical Engineering Medi-Caps University Indore AB M.P. Indore452001 India Department of ECE Mahatma Gandhi Institute of Technology Telangana Hyderabad India

ISBN: (纸本)9798350305418

With the rapid development of industry, the types and quantities of wastewater have increased rapidly, and the pollution to water bodies has become increasingly widespread and serious. As far as water system is concerned, the information of water quality system is both known and unknown because of incomplete data information and great uncertainty of systematic observation information, such as data error, data quality and quantity influence, etc. Therefore, judging from the clarity of system information, water quality pollution assessment is actually a problem with definite extension but uncertain connotation. In this paper, a water quality detection method based on grey clustering algorithm is proposed to evaluate the treatment effect of industrial wastewater by magnetic resin adsorption, and the effectiveness of the proposed method is verified by comparative experiments. The results show that grey clustering algorithm can deal with the measured data of turbidity, dissolved oxygen and conductivity of water quality parameters without changing the basic trend of the measured data, and at the same time, it can remove some noise signals to get a smoother data curve. Through the analysis of practical data and the comparison of traditional water quality evaluation models, the prediction algorithm predicts the change trend of water turbidity more effectively, and improves the accuracy of water turbidity control in the process of water treatment. © 2023 IEEE.

关键词： grey clustering algorithm Industrial wastewater Magnetic resin Testing water quality

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Mental Health Intelligent Evaluation System based on grey clustering algorithm

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Procedia Computer Science 2024年 247卷 1110-1119页

作者： Di Li College of Physical Education Bohai University Jinzhou China

关键词： grey clustering algorithm Mental Health Analysis And Evaluation Whitening Weight Function Mathematical Model

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Risk Evaluation Of Expressway PFI Construction Project Based On the Analytic Hierarchy Process and grey clustering

Risk Evaluation Of Expressway PFI Construction Project Based...

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作者： HONG Wen-xia WEI Xiao-zhao YANG Fan Qingdao University of Technology

This paper analyzes the advantages of PFI project and the feasibility of highway construction project, analyzes the risk factors and the project stakeholders, and establishes the risk factors involved in the construction project, and establishes a risk assessment system, and uses the analytic hierarchy process to calculate the weight of the evaluation index, and then improve the objectivity of the evaluation system. The main body of the financing is involved in the cluster analysis, quantitative analysis, and through the gray clustering algorithm to evaluate the risk index value, and finally quantitative analysis of PFI financing mode in the highway construction projects in the use of integrated risk.

关键词： analytic hierarchy process grey clustering algorithm PFI financing model highway project

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Studying on the life cycle information share and discovery for complicated products based on data mining and data grid technology

Studying on the life cycle information share and discovery f...

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12th International Manufacturing Conference in China

作者： Fang, Xifeng Zhao, Liangcai Su, Shijie Jiangsu Univ Sci & Technol Zhenjiang 212003 Jiangsu Peoples R China

ISBN: (纸本)9780878494217

Complicated product lifecycle information including design and manufacturing, operation and maintenance as well as relative supply information, all are tightly related to the product life cycle cooperative design and the process of establishing the dynamic alliance. Data grid includes the digital library and data grid service technologies and it can provide the reliable technique support to integrated information systems. The grey clustering is used to merge the same type of factors based on presetting conditions. The improved grey clustering algorithm has been used to find the main failure types for some equipment. The structure of the multi layers and cross information share in the dynamic alliance for the ship life cycle information based on two data grid service centers and the flows of resources and information discovery based on data mining are proposed according to the information share requirements. A developed protocol system based on two data grid services has been presented to show ship lifecycle information share and finding the main failure types of pumps using grey clustering algorithm.

关键词： data mining grey clustering algorithm data grid technology information share and discovery

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