Industrial Efficiency Algorithm Based on Spatio-Temporal-Data-Driven
Stochastic frontier model is an important and effective method to calculate industry efficiency. However, when dealing with temporal and spatial data from the industry, it is difficult to accurately calculate the industrial production efficiency due to the influence of spatial correlation and time l...
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2021
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oai:doaj.org-article:dde841e1909545978bbd2eb8f0395e612021-11-22T01:09:32ZIndustrial Efficiency Algorithm Based on Spatio-Temporal-Data-Driven1530-867710.1155/2021/7439744https://doaj.org/article/dde841e1909545978bbd2eb8f0395e612021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/7439744https://doaj.org/toc/1530-8677Stochastic frontier model is an important and effective method to calculate industry efficiency. However, when dealing with temporal and spatial data from the industry, it is difficult to accurately calculate the industrial production efficiency due to the influence of spatial correlation and time lag effect. If the traditional spatial statistical method is used, the setting method of spatial weight matrix is often questioned. To solve this series of problems, one possible idea is to design a spatial data mining process based on stochastic frontier analysis. Firstly, the stochastic frontier model should be improved to analyze spatio-temporal data. In order to accurately measure the technical efficiency in the case of dual correlation between time and space, a more effective spatio-temporal stochastic frontier model method is proposed. Meanwhile, based on the idea of generalized moment estimation, an estimation method of spatiotemporal stochastic frontier model is designed, and the consistency of estimators is proved. In order to ensure that the most appropriate spatial weight matrix can be selected in the process of model construction, the K-fold crossvalidation method is adopted to evaluate the prediction effect under the data-driven idea. This set of spatio-temporal data mining methods will be used to measure the technical efficiency of high-tech industries in various provinces of China.Hongqu LvWensi ChengHindawi-WileyarticleTechnologyTTelecommunicationTK5101-6720ENWireless Communications and Mobile Computing, Vol 2021 (2021) |
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Technology T Telecommunication TK5101-6720 |
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Technology T Telecommunication TK5101-6720 Hongqu Lv Wensi Cheng Industrial Efficiency Algorithm Based on Spatio-Temporal-Data-Driven |
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Stochastic frontier model is an important and effective method to calculate industry efficiency. However, when dealing with temporal and spatial data from the industry, it is difficult to accurately calculate the industrial production efficiency due to the influence of spatial correlation and time lag effect. If the traditional spatial statistical method is used, the setting method of spatial weight matrix is often questioned. To solve this series of problems, one possible idea is to design a spatial data mining process based on stochastic frontier analysis. Firstly, the stochastic frontier model should be improved to analyze spatio-temporal data. In order to accurately measure the technical efficiency in the case of dual correlation between time and space, a more effective spatio-temporal stochastic frontier model method is proposed. Meanwhile, based on the idea of generalized moment estimation, an estimation method of spatiotemporal stochastic frontier model is designed, and the consistency of estimators is proved. In order to ensure that the most appropriate spatial weight matrix can be selected in the process of model construction, the K-fold crossvalidation method is adopted to evaluate the prediction effect under the data-driven idea. This set of spatio-temporal data mining methods will be used to measure the technical efficiency of high-tech industries in various provinces of China. |
format |
article |
author |
Hongqu Lv Wensi Cheng |
author_facet |
Hongqu Lv Wensi Cheng |
author_sort |
Hongqu Lv |
title |
Industrial Efficiency Algorithm Based on Spatio-Temporal-Data-Driven |
title_short |
Industrial Efficiency Algorithm Based on Spatio-Temporal-Data-Driven |
title_full |
Industrial Efficiency Algorithm Based on Spatio-Temporal-Data-Driven |
title_fullStr |
Industrial Efficiency Algorithm Based on Spatio-Temporal-Data-Driven |
title_full_unstemmed |
Industrial Efficiency Algorithm Based on Spatio-Temporal-Data-Driven |
title_sort |
industrial efficiency algorithm based on spatio-temporal-data-driven |
publisher |
Hindawi-Wiley |
publishDate |
2021 |
url |
https://doaj.org/article/dde841e1909545978bbd2eb8f0395e61 |
work_keys_str_mv |
AT hongqulv industrialefficiencyalgorithmbasedonspatiotemporaldatadriven AT wensicheng industrialefficiencyalgorithmbasedonspatiotemporaldatadriven |
_version_ |
1718418431416467456 |