Intelligent data aggregation inspired paradigm and approaches in IoT applications

Yuan, Xiaohui; Elhoseny, Mohamed

doi:10.3233/jifs-179057

Cited by 5 publications

(2 citation statements)

References 47 publications

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“…Social security funds through a cloud of audit, pointing to will and the framework of cloud computing technologies into the social security fund audit work, making all kinds of audit resource synergy through clouds, will be a large number of social security funds audit data collected in a unified platform for integration management and reasonable scheduling, to help the auditor to further improve the work efficiency and reduce audit risk [3]. e cloud audit service of social security funds can achieve the coordinated development of audit departments at all levels to a certain extent, reduce the development cost of audit software, improve the work efficiency of audit services, and play a certain role in promoting the development of social security fund audit in China.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Construction of Social Security Fund Cloud Audit Platform Based on Fuzzy Data Mining Algorithm

Huai

Zhang

2021

Complexity

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Guided by the theories of system theory, synergetic theory, and other disciplines and based on fuzzy data mining algorithm, this article constructs a three-tier social security fund cloud audit platform. Firstly, the article systematically expounds the current situation of social security fund and social security fund audit, such as the technical basis of cloud computing and data mining. Combined with the actual work, the necessity and feasibility of building a cloud audit platform for social security funds are analyzed. This article focuses on the construction of the cloud audit platform for social security funds. The general idea of using fuzzy data mining algorithm to build the social security fund audit cloud platform is to compress the knowledge contained in a large number of data into the weights between nodes and optimize the weights through the learning of the neural network system. Through the optimization function, the information contained in the neural network is stored in a few weights as far as possible. The main information is further highlighted by network clipping and removing weights that have little impact on the output.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Construction of Social Security Fund Cloud Audit Platform Based on Fuzzy Data Mining Algorithm

Huai

Zhang

2021

Complexity

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“…Literature [ 10 ] proposed the prospect of mobile development of LBS business and the strategy of LBS application innovation through the SWOT analysis model and carried out a simple LBS system planning and design for the industrial application of LBS personal products with practical needs. Reference [ 11 ] builds an LBS group buying business adoption model and verifies the hypothesis that perceived trust, perceived usefulness and ease of use, and network externalities are important factors that affect the willingness to use LBS group buying. Literature [ 12 ] uses theoretical analysis tools and data analysis reports of mobile operators and consulting companies to analyze and study the development status, influencing factors, profit models, and development trends of the LBS industry, promotes the development of the LBS industry, and provides suggestion on characteristics of electronic services.…”

Section: Related Workmentioning

confidence: 99%

Continuous Use Intention of Mobile Social Network Information Service Based on User Behavior Perception

Jing-jing

Wang

Yin

et al. 2022

Computational Intelligence and Neuroscience

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In order to improve the willingness of continuous use of mobile social network information services, this study combines user behavior perception to analyze the continuous use of mobile social network information services and proposes a data coverage optimization strategy based on service quality perception. Furthermore, this study measures participants’ regional preferences based on the duration of participants in the perceptual region and the number of historical perceptual tasks completed on the perceptual region. In addition, this study designs a perceptual data coverage optimization algorithm to optimize the perceptual data coverage and ensure the real-time validity of the perceptual data. Through algorithm research and systematic evaluation, it can be seen that the continuous use willingness system of mobile social network information service based on user behavior perception can basically meet the actual needs.

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Data Mining Algorithm for Cloud Network Information Based on Artificial Intelligence Decision Mechanism

et al. 2020

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Due to the rapid development of information technology and network technology, there is a lot of data, but the phenomenon of lack of knowledge is becoming more and more serious. Data mining technology has developed vigorously in this environment, and it has shown more and more vitality. Based on Spark programming model, this paper designs the parallel extension of fuzzy c-means. In order to enhance the performance of fuzzy c-means parallel expansion, the improvement strategy of k-means during the initialization phase is borrowed, and k-means// is extended to fuzzy c-means to obtain better clustering performance. Combined with Spark's programming model, this paper can obtain extended parallel fuzzy c-means algorithm. Several experiments on the data set of the algorithm proposed in this paper have shown good scalability and parallelism, effectively expanding fuzzy c-means clustering to distributed applications, greatly increasing the scale of the data processed by the algorithm. This improves the robustness of the algorithm and the adaptability of the algorithm to the shape and structure of the data, so that the parallel and scalable clustering algorithm can more effectively perform cluster analysis on big data. Three algorithms were simulated on MATLAB platform. We use simple data sets and complex two-dimensional data sets, and compare with the traditional fuzzy c-means algorithm and fuzzy c-means algorithm based on fuzzy entropy. Experiments show that the scalable parallel fuzzy c-means algorithm not only greatly improves the anti-noise performance, but also improves the convergence speed, and it can automatically determine the optimal number of clusters. INDEX TERMS Artificial intelligence, data mining, cluster analysis, scalable parallel fuzzy c-means, cloud computing.

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Intelligent data aggregation inspired paradigm and approaches in IoT applications

Cited by 5 publications

References 47 publications

[Retracted] Construction of Social Security Fund Cloud Audit Platform Based on Fuzzy Data Mining Algorithm

[Retracted] Construction of Social Security Fund Cloud Audit Platform Based on Fuzzy Data Mining Algorithm

Continuous Use Intention of Mobile Social Network Information Service Based on User Behavior Perception

Data Mining Algorithm for Cloud Network Information Based on Artificial Intelligence Decision Mechanism

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