The nonlinear time lag multivariable grey prediction model based on interval grey numbers and its application

被引:0
作者
Pingping Xiong
Xia Zou
Yingjie Yang
机构
[1] Nanjing University of Information Science and Technology,School of Management Science and Engineering
[2] Nanjing University of Information Science and Technology,Jiangsu Statistical Science Research Base
[3] Nanjing University of Information Science and Technology,College of Mathematics and Statistics
[4] De Montfort University,Institute of Artificial Intelligence
来源
Natural Hazards | 2021年 / 107卷
关键词
Grey system; Interval grey number; Nonlinear; Time lag; Smog;
D O I
暂无
中图分类号
学科分类号
摘要
The linear relationship of the original grey prediction model is too single, and the original grey prediction model does not consider the time delay of the effect of the current input parameters on the output parameters. In order to solve these problems, the interval grey number sequence is taken as the modelling sequence of the model, and the nonlinear parameter γ and the time-delay parameter τ are introduced into the multivariate grey prediction model, so as to construct the nonlinear time-delay multivariable grey prediction model for interval grey number. In view of the uncertain characteristics of the smog index data, this paper applies the improved model to the simulation and prediction of the smog index data. Compared with the original model, the results show that the prediction effect of the model proposed in this paper is superior to the original model in terms of its effectiveness and feasibility.
引用
收藏
页码:2517 / 2531
页数:14
相关论文
共 46 条
[1]  
Camelia D(2015)Grey systems theory in economics—bibliometric analysis and applications’ overview Grey Syst Theory Appl 5 244-262
[2]  
Cui LZ(2008)MGM(1, n) based on vector continued fractions theory Syst Eng 26 47-51
[3]  
Liu SF(2015)Haze pollution and its control measures based on statistical method J Xiamen Univ Nat Sci 54 114-121
[4]  
Wu ZP(2016)Research on haze prediction based on multivariate linear regression Comput Sci 43 526-528
[5]  
Feng SR(2013)Study on the causes, harms and preventive measures of Haze weather Resour Econo Environ Protect 10 146-132
[6]  
Fu JY(2020)A novel grey model with a three-parameter background value and its application in forecasting average annual water consumption per capita in urban areas along the Yangtze River Basin J Grey Syst 32 118-316
[7]  
Li JL(2010)Algorithm rules of interval grey numbers based on the “Kernel” and the degree of greyness of grey numbers Syst Eng Electron 32 313-62
[8]  
Li SL(2017)A novel kernel regularized nonhomogeneous grey model and its applications Commun Nonlinear Sci Numer Simul 48 51-638
[9]  
Zeng B(2020)Logistics forecast of malacca strait port using grey GM(1,N) model J Coast Res 103 634-810
[10]  
Ma X(2011)Optimization of background value in MGM(1,m) model Control Decis 26 806-188