E-Commerce Enterprise Supply Chain Financing Risk Assessment Based on Linked Data Mining and Edge Computing

Qu, Qiao; Liu, Cheng; Bao, Xiaoqian

doi:10.1155/2021/9938325

Cited by 16 publications

(8 citation statements)

References 50 publications

(38 reference statements)

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“…e inspection method is the same as that of the vertical decision-making pole. e search system is a part of the office system, and the activity diagram is shown in Figure 4 [15].…”

Section: Activity Diagram Of Supervision Systemmentioning

confidence: 99%

Design and Research of a Government Affairs Office Platform

Chen

Jingbo

2021

Mobile Information Systems

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Recent advancements in Digital Communication Systems and Web Technology tendered information systems cheaper and allow people to move into the electronic Government (eGov) platforms. eGov is the use of information and communication technologies (ICTs), whereas good governance refers to how well public authorities manage public and social resources. eGov supports excellent governance practices, yet it also has certain limitations. In this article, we enhance the study of Jiyuan City’s Internet-based e-government system based on an analysis of theoretical knowledge and application state. First, we gathered all government affairs platform websites; then, we built the supervision system function code in accordance with the supervision system activity diagram. Finally, the office platform's system deployment was completed, and the government office platform’s analysis environment was provided, and it was validated via experiments. The experimental results show that when there are 300 government affairs tasks to be handled, the data recall rate of the design platform’s government affairs website is 95%, and the design platform’s government affairs processing time is 15 minutes. The proposed government affairs platform has a high processing efficiency and data-carrying capacity.

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“…e inspection method is the same as that of the vertical decision-making pole. e search system is a part of the office system, and the activity diagram is shown in Figure 4 [15].…”

Section: Activity Diagram Of Supervision Systemmentioning

confidence: 99%

Design and Research of a Government Affairs Office Platform

Chen

Jingbo

2021

Mobile Information Systems

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“…Wu and Nagahashi [ 20 ] used the grey forecasting model to carry out human resource forecasting analysis for enterprises, which provided a reference for its human resource planning. Qu et al [ 21 ] predicted the human resources of enterprises based on backpropagation neural network (BPNN) and believed that network can obtain better prediction results. There are many factors affecting human resource demand and non-linear correlation.…”

Section: Introductionmentioning

confidence: 99%

“…erefore, common predictive analysis methods cannot truly reflect the nature of the problem. As a remedy, researchers began to study prediction methods based on machine learning models, which have higher superiority compared with traditional prediction methods [21][22][23][24][25]. Common modern machine learning methods include BPNN, K-nearest neighbors (KNN), support vector machine (SVM), and so on.…”

Section: Introductionmentioning

confidence: 99%

Human Resource Planning and Configuration Based on Machine Learning

Yuan

Dai

et al. 2022

Computational Intelligence and Neuroscience

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Human resources are the core resources of an enterprise, and the demand forecasting plays a vital role in the allocation and optimization of human resources. Starting from the basic concepts of human resource forecasting, this paper employs the backpropagation neural network (BPNN) and radial basis function neural network (RBFNN) to analyze human resource needs and determine the key elements of the company’s human resource allocation through predictive models. With historical data as reference, the forecast value of current human resource demand is obtained through the two types of neural networks. Based on the prediction results, the company managers can carry out targeted human resource planning and allocation to improve the efficiency of enterprise operations. In the experiment, the actual human resource data of a certain company are used as the experimental basic samples to train and test the two types of machine learning tools. The experimental results show that the method proposed in this paper can effectively predict the number of personnel required and can support the planning and allocation of human resources.

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“…The influence of consumer psychology and other factors on shopping decision-making. Qu et al [ 11 ] applied the advantages of edge computing methods to the evaluation framework of the e-commerce supply chain. At the same time, this model can establish a fuzzy neural network based on the supply chain.…”

Section: Introductionmentioning

confidence: 99%

E-Commerce Information System Management Based on Data Mining and Neural Network Algorithms

Zhang

Abdullah

Chong

et al. 2022

Computational Intelligence and Neuroscience

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The rapid development of artificial intelligence technology has led to rapid development in various fields. It has many hidden related customer behavior information and future development trends in the e-commerce information system. The data mining technology can dig out useful information and promote the development of e-commerce. This research analyzes the significance and advantages of data mining technology in the application of e-commerce management systems and analyzes the related technologies of data mining and future trend prediction. This research has taken the advantages of clustering and naive Bayesian methods in data mining to classify product information and purchase preferences and other information and mine the associated data. Then, the nonlinear data processing advantages of neural networks are used to predict future purchasing power. The results show that data mining technology and neural networks have high accuracy in predicting future consumer purchasing power information. The correlation coefficient between real consumption data and predicted consumption data reached 0.9785, and the maximum relative average error was only 2.32%. It fully shows that data mining technology can obtain some unrecognizable related information and future consumption trends in e-commerce systems, and neural networks can also predict future consumption power and consumption patterns well.

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E-Commerce Enterprise Supply Chain Financing Risk Assessment Based on Linked Data Mining and Edge Computing

Cited by 16 publications

References 50 publications

Design and Research of a Government Affairs Office Platform

Design and Research of a Government Affairs Office Platform

Human Resource Planning and Configuration Based on Machine Learning

E-Commerce Information System Management Based on Data Mining and Neural Network Algorithms

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