Nonlinear Grey Prediction Model with Convolution Integral NGMC (1,n) and Its Application to the Forecasting of China’s Industrial SO2 Emissions

The grey prediction model with convolution integral GMC (1, n) is a multiple grey model with exact solutions. To further improve prediction accuracy and describe better the relationship between cause and effect, we introduce nonlinear parameters into GMC (1, n) model and additionally apply a convolu...

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Main Author: Zheng-Xin Wang
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2014/580161
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author Zheng-Xin Wang
author_facet Zheng-Xin Wang
author_sort Zheng-Xin Wang
collection DOAJ
description The grey prediction model with convolution integral GMC (1, n) is a multiple grey model with exact solutions. To further improve prediction accuracy and describe better the relationship between cause and effect, we introduce nonlinear parameters into GMC (1, n) model and additionally apply a convolution integral to produce an improved forecasting model here designated as NGMC (1, n). The model solving process applied the least-squares method to evaluate the structure parameters of the model: convolution was used to obtain an exact solution with this improved grey model. The nonlinear optimisation took the parameters as the decision variables with the objective of minimising forecasting errors. The GMC (1, 2) and NGMC (1, 2) models were used to predict China’s industrial SO2 emissions from the basis of the economic output level as the influencing factor. Results indicated that NGMC (1, 2) can effectively describe the nonlinear relationship between China’s economic output and SO2 emissions with an improved accuracy over current GMC (1, 2) models.
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spelling doaj-art-3e03214e7af14890ba82e0a9890917db2025-08-20T02:08:23ZengWileyJournal of Applied Mathematics1110-757X1687-00422014-01-01201410.1155/2014/580161580161Nonlinear Grey Prediction Model with Convolution Integral NGMC (1,n) and Its Application to the Forecasting of China’s Industrial SO2 EmissionsZheng-Xin Wang0School of Economics & International Trade, Zhejiang University of Finance & Economics, Hangzhou, Zhejiang 310018, ChinaThe grey prediction model with convolution integral GMC (1, n) is a multiple grey model with exact solutions. To further improve prediction accuracy and describe better the relationship between cause and effect, we introduce nonlinear parameters into GMC (1, n) model and additionally apply a convolution integral to produce an improved forecasting model here designated as NGMC (1, n). The model solving process applied the least-squares method to evaluate the structure parameters of the model: convolution was used to obtain an exact solution with this improved grey model. The nonlinear optimisation took the parameters as the decision variables with the objective of minimising forecasting errors. The GMC (1, 2) and NGMC (1, 2) models were used to predict China’s industrial SO2 emissions from the basis of the economic output level as the influencing factor. Results indicated that NGMC (1, 2) can effectively describe the nonlinear relationship between China’s economic output and SO2 emissions with an improved accuracy over current GMC (1, 2) models.http://dx.doi.org/10.1155/2014/580161
spellingShingle Zheng-Xin Wang
Nonlinear Grey Prediction Model with Convolution Integral NGMC (1,n) and Its Application to the Forecasting of China’s Industrial SO2 Emissions
Journal of Applied Mathematics
title Nonlinear Grey Prediction Model with Convolution Integral NGMC (1,n) and Its Application to the Forecasting of China’s Industrial SO2 Emissions
title_full Nonlinear Grey Prediction Model with Convolution Integral NGMC (1,n) and Its Application to the Forecasting of China’s Industrial SO2 Emissions
title_fullStr Nonlinear Grey Prediction Model with Convolution Integral NGMC (1,n) and Its Application to the Forecasting of China’s Industrial SO2 Emissions
title_full_unstemmed Nonlinear Grey Prediction Model with Convolution Integral NGMC (1,n) and Its Application to the Forecasting of China’s Industrial SO2 Emissions
title_short Nonlinear Grey Prediction Model with Convolution Integral NGMC (1,n) and Its Application to the Forecasting of China’s Industrial SO2 Emissions
title_sort nonlinear grey prediction model with convolution integral ngmc 1 n and its application to the forecasting of china s industrial so2 emissions
url http://dx.doi.org/10.1155/2014/580161
work_keys_str_mv AT zhengxinwang nonlineargreypredictionmodelwithconvolutionintegralngmc1nanditsapplicationtotheforecastingofchinasindustrialso2emissions