Learning regularity in an economic time-series for structure prediction

Bhattacharya, Diptendu; Mukhoti, Jishnu; Konar, Amit

doi:10.1016/j.asoc.2018.12.003

Cited by 27 publications

(14 citation statements)

References 45 publications

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“…Based on the unit root test and the cointegration test, the literature [6] used panel data of per capita real GDP to construct an individual time-point two-way fixed effect model to conduct an empirical analysis of the relationship between the development of the Internet industry and economic growth. e literature [7] used the spatial weight matrix of inter-regional trade correlation to systematically measure the spillover effect of the Internet industry on the production level, export level, and wage level of other regions. e results show that the development of the Internet industry has a positive effect on the growth of this region and other regions.…”

Section: Related Workmentioning

confidence: 99%

Economic Market Fluctuation Model Based on Internet of Things Technology

Zhai

2022

Scientific Programming

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In order to explore the impact of the Internet of Things technology on economic market fluctuations and the analysis effect of the Internet of Things technology on economic market fluctuations, this paper uses the Internet of Things algorithm to improve the economic fluctuation model. Moreover, this paper uses the Internet of Things algorithm to locate economic transactions and performs data processing to optimize the intelligent network system to improve the operating effect of the economic system. In addition, this paper improves the sensor node algorithm and proposes to use the weighted value of network node density to balance the positioning problem caused by the unbalanced distribution of network nodes in the detection area. Finally, this paper analyzes the market economy volatility model through the Internet of Things technology, combined with simulation experiments to explore the application of the Internet of Things technology in the economic market volatility model. Through experimental research, it can be known that economic market fluctuation models based on Internet of Things technology can play an important role in market economic analysis.

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Section: Related Workmentioning

confidence: 99%

Economic Market Fluctuation Model Based on Internet of Things Technology

Zhai

2022

Scientific Programming

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“…e literature [4] introduced the project responsibility cost control method into the engineering project cost management, explained the reasons for choosing this method, and discussed the advantages and disadvantages of the project responsibility cost control method applied to the engineering project. e literature [5] analyzed the theoretical basis of the earned value method and applied it in practice in the project of Hunan International Convention and Exhibition Center. e literature [6] proposed a multifactor cost analysis model based on Analytic Hierarchy Process (AHP).…”

Section: Related Workmentioning

confidence: 99%

Application of Data Mining Technology in Field Verification of Project Cost

Jiang

2021

Advances in Multimedia

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The traditional budget quota pricing model seems incompatible with the continuous development of the market economy. Low degree of visualization, extensive resource management, difficulty in collecting construction data, lagging control work, and separation of cost control from project management have become the main problems of current construction project cost control. This paper combines data mining technology to improve the project cost on-site verification network system, build a project cost verification system that can be used for on-site verification, and build a cost information platform. Moreover, this paper makes full use of computer information technology and uses the local area network and network as the basis to transform the vertical transmission of cost information into horizontal, so as to ensure the effective communication and exchange of cost information. According to the analysis of the case study, it can be seen that the project cost field verification method based on data mining proposed in this paper is very effective, and the system proposed in this paper can be used in actual projects.

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“…The results show that the rural economic environment, rural financial environment, rural policy environment, and rural credit environment can significantly reduce the vulnerability of new rural financial institutions. The literature [10] studied the regional differences of rural financial ecological environment by constructing a system dynamics model. The research results show that the rural financial ecological environment in the eastern region is the best, the central and western regions are in the middle, and the eastern region is the worst.…”

Section: Related Workmentioning

confidence: 99%

“…First, the model extracts the data of various rural financial ecological environment evaluation indicators, and then performs missing value processing, outlier elimination, standardization processing, and normalization processing on the data. In this paper, formula (10) is used to forward the reverse index, and formula ( 11) is used to forward the moderate index.…”

Section: Related Workmentioning

confidence: 99%

Evaluation of rural financial ecological environment based on machine learning and improved neural network

Wen

Zhang

2021

Neural Comput & Applic

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In order to improve the effect of rural financial ecological environment evaluation, this paper combines machine learning and improved neural network algorithms to construct a rural financial ecological environment evaluation system. First, this paper optimizes the input layer structure and its initial weight random assignment. The input layer structure is processed by factor analysis, and the initial weight random assignment is optimized by particle swarm optimization. Secondly, this paper constructs a rural financial ecological environment evaluation model based on factor analysis method and PSO-SOM to avoid the defects of traditional SOM algorithm used in financial ecological environment evaluation research. Finally, this paper constructs a system framework based on actual needs and designs experiments to verify the performance of the evaluation system constructed in this paper. The research results show that the system constructed in this paper meets the basic needs of rural financial ecological environment evaluation.

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Learning regularity in an economic time-series for structure prediction

Cited by 27 publications

References 45 publications

Economic Market Fluctuation Model Based on Internet of Things Technology

Economic Market Fluctuation Model Based on Internet of Things Technology

Application of Data Mining Technology in Field Verification of Project Cost

Evaluation of rural financial ecological environment based on machine learning and improved neural network

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