Parameter Optimization on the Three-Parameter Whitenization Grey Model and Its Application in Simulation and Prediction of Gross Enrollment Rate of Higher Education in China
The gray prediction model, based on the GM(1,1) method, is an important branch of gray theory with the most active research and the most fruitful results, and it is the most widely used because of its small sample size, simple modeling process, and easy to use. Such advantages have been successfully...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/6640000 |
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| _version_ | 1832567741664460800 |
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| author | Jihong Sun Hui Li Bo Zeng Xiaoyun Zhao Chuanhui Wang |
| author_facet | Jihong Sun Hui Li Bo Zeng Xiaoyun Zhao Chuanhui Wang |
| author_sort | Jihong Sun |
| collection | DOAJ |
| description | The gray prediction model, based on the GM(1,1) method, is an important branch of gray theory with the most active research and the most fruitful results, and it is the most widely used because of its small sample size, simple modeling process, and easy to use. Such advantages have been successfully applied in many fields such as transportation, agriculture, energy, medicine, and environment and have been gradually developed into a mainstream predictive modeling method. This study combines the Three-parameter Whitenization Grey Model (TWGM(1,1)), which fits the inhomogeneous exponential law sequence, and the Particle Swarm Algorithm (PSA) to optimize the order and background value coefficients under the condition of the minimum sum of squares of simulation errors, and hence, to solve the problem that the cumulative order is fixed to “1” and the background value coefficient value is fixed to “0.5.” As a result, a parameter-optimized gray system model with flexibility, adaptability, and dynamic adjustment is designed to simulate and predict China’s higher education gross enrollment rate. The application shows that the model has better overall simulation and prediction performance than others. On the one hand, the parametric optimization model significantly improves its own performance, and on the other hand, its intelligent and adjustable adaptivity improves the accuracy and further extends its application. |
| format | Article |
| id | doaj-art-91edab3c76ca407594cf3c249ae6d5cf |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-91edab3c76ca407594cf3c249ae6d5cf2025-02-03T01:00:41ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/66400006640000Parameter Optimization on the Three-Parameter Whitenization Grey Model and Its Application in Simulation and Prediction of Gross Enrollment Rate of Higher Education in ChinaJihong Sun0Hui Li1Bo Zeng2Xiaoyun Zhao3Chuanhui Wang4Center of High Education, National Institution of Education Science, Beijing 100088, ChinaCollege of Mathematics and Statistics, Chongqing Technology and Bussiness University, Chongqing 400067, ChinaCollege of Mathematics and Statistics, Chongqing Technology and Bussiness University, Chongqing 400067, ChinaCollege of Economics, Qufu Normal University, Rizhao 276800, ChinaCollege of Economics, Qufu Normal University, Rizhao 276800, ChinaThe gray prediction model, based on the GM(1,1) method, is an important branch of gray theory with the most active research and the most fruitful results, and it is the most widely used because of its small sample size, simple modeling process, and easy to use. Such advantages have been successfully applied in many fields such as transportation, agriculture, energy, medicine, and environment and have been gradually developed into a mainstream predictive modeling method. This study combines the Three-parameter Whitenization Grey Model (TWGM(1,1)), which fits the inhomogeneous exponential law sequence, and the Particle Swarm Algorithm (PSA) to optimize the order and background value coefficients under the condition of the minimum sum of squares of simulation errors, and hence, to solve the problem that the cumulative order is fixed to “1” and the background value coefficient value is fixed to “0.5.” As a result, a parameter-optimized gray system model with flexibility, adaptability, and dynamic adjustment is designed to simulate and predict China’s higher education gross enrollment rate. The application shows that the model has better overall simulation and prediction performance than others. On the one hand, the parametric optimization model significantly improves its own performance, and on the other hand, its intelligent and adjustable adaptivity improves the accuracy and further extends its application.http://dx.doi.org/10.1155/2020/6640000 |
| spellingShingle | Jihong Sun Hui Li Bo Zeng Xiaoyun Zhao Chuanhui Wang Parameter Optimization on the Three-Parameter Whitenization Grey Model and Its Application in Simulation and Prediction of Gross Enrollment Rate of Higher Education in China Complexity |
| title | Parameter Optimization on the Three-Parameter Whitenization Grey Model and Its Application in Simulation and Prediction of Gross Enrollment Rate of Higher Education in China |
| title_full | Parameter Optimization on the Three-Parameter Whitenization Grey Model and Its Application in Simulation and Prediction of Gross Enrollment Rate of Higher Education in China |
| title_fullStr | Parameter Optimization on the Three-Parameter Whitenization Grey Model and Its Application in Simulation and Prediction of Gross Enrollment Rate of Higher Education in China |
| title_full_unstemmed | Parameter Optimization on the Three-Parameter Whitenization Grey Model and Its Application in Simulation and Prediction of Gross Enrollment Rate of Higher Education in China |
| title_short | Parameter Optimization on the Three-Parameter Whitenization Grey Model and Its Application in Simulation and Prediction of Gross Enrollment Rate of Higher Education in China |
| title_sort | parameter optimization on the three parameter whitenization grey model and its application in simulation and prediction of gross enrollment rate of higher education in china |
| url | http://dx.doi.org/10.1155/2020/6640000 |
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