A Novel Optimized Nonlinear Grey Bernoulli Model for Forecasting China’s GDP
The nonlinear grey Bernoulli model, abbreviated as NGBM(1,1), has been successfully applied to control, prediction, and decision-making fields, especially in the prediction of nonlinear small sample time series. However, there are still some problems in improving the prediction accuracy of NGBM(1,1)...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
|
| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2019/1731262 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832545377180450816 |
|---|---|
| author | Wen-Ze Wu Tao Zhang Chengli Zheng |
| author_facet | Wen-Ze Wu Tao Zhang Chengli Zheng |
| author_sort | Wen-Ze Wu |
| collection | DOAJ |
| description | The nonlinear grey Bernoulli model, abbreviated as NGBM(1,1), has been successfully applied to control, prediction, and decision-making fields, especially in the prediction of nonlinear small sample time series. However, there are still some problems in improving the prediction accuracy of NGBM(1,1). In this paper, we propose a novel optimized nonlinear grey Bernoulli model for forecasting Chinaʼs GDP. In the new model, the structure and parameters of NGBM(1,1) are optimized simultaneously. Especially, the latest item of first-order accumulative generating operator (1-AGO) sequence is taken as the initial condition, then background value is reconstructed by optimizing weights of neighbor values in 1-AGO sequence, which is based on minimizing the sum of absolute percentage errors, and finally, we establish the new model based on the rolling mechanism. Prediction accuracy of the proposed model is investigated through some simulations and a real example application, and the proposed model is applied to forecast the annual GDP in China from 2019 to 2023. |
| format | Article |
| id | doaj-art-7c23653e9ad84a409653f78f42dfd11b |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-7c23653e9ad84a409653f78f42dfd11b2025-02-03T07:25:55ZengWileyComplexity1076-27871099-05262019-01-01201910.1155/2019/17312621731262A Novel Optimized Nonlinear Grey Bernoulli Model for Forecasting China’s GDPWen-Ze Wu0Tao Zhang1Chengli Zheng2School of Economics and Business Administration, Central China Normal University, Wuhan 430079, ChinaSchool of Science, Guangxi University of Science and Technology, Liuzhou 545006, ChinaSchool of Economics and Business Administration, Central China Normal University, Wuhan 430079, ChinaThe nonlinear grey Bernoulli model, abbreviated as NGBM(1,1), has been successfully applied to control, prediction, and decision-making fields, especially in the prediction of nonlinear small sample time series. However, there are still some problems in improving the prediction accuracy of NGBM(1,1). In this paper, we propose a novel optimized nonlinear grey Bernoulli model for forecasting Chinaʼs GDP. In the new model, the structure and parameters of NGBM(1,1) are optimized simultaneously. Especially, the latest item of first-order accumulative generating operator (1-AGO) sequence is taken as the initial condition, then background value is reconstructed by optimizing weights of neighbor values in 1-AGO sequence, which is based on minimizing the sum of absolute percentage errors, and finally, we establish the new model based on the rolling mechanism. Prediction accuracy of the proposed model is investigated through some simulations and a real example application, and the proposed model is applied to forecast the annual GDP in China from 2019 to 2023.http://dx.doi.org/10.1155/2019/1731262 |
| spellingShingle | Wen-Ze Wu Tao Zhang Chengli Zheng A Novel Optimized Nonlinear Grey Bernoulli Model for Forecasting China’s GDP Complexity |
| title | A Novel Optimized Nonlinear Grey Bernoulli Model for Forecasting China’s GDP |
| title_full | A Novel Optimized Nonlinear Grey Bernoulli Model for Forecasting China’s GDP |
| title_fullStr | A Novel Optimized Nonlinear Grey Bernoulli Model for Forecasting China’s GDP |
| title_full_unstemmed | A Novel Optimized Nonlinear Grey Bernoulli Model for Forecasting China’s GDP |
| title_short | A Novel Optimized Nonlinear Grey Bernoulli Model for Forecasting China’s GDP |
| title_sort | novel optimized nonlinear grey bernoulli model for forecasting china s gdp |
| url | http://dx.doi.org/10.1155/2019/1731262 |
| work_keys_str_mv | AT wenzewu anoveloptimizednonlineargreybernoullimodelforforecastingchinasgdp AT taozhang anoveloptimizednonlineargreybernoullimodelforforecastingchinasgdp AT chenglizheng anoveloptimizednonlineargreybernoullimodelforforecastingchinasgdp AT wenzewu noveloptimizednonlineargreybernoullimodelforforecastingchinasgdp AT taozhang noveloptimizednonlineargreybernoullimodelforforecastingchinasgdp AT chenglizheng noveloptimizednonlineargreybernoullimodelforforecastingchinasgdp |