Abstract
China’s increasing energy consumption poses challenges to economy and environment. How to predict the energy consumption accurately and regulate the future energy consumption production is a problem worth studying. In this paper, the fractional order cumulative linear time-varying parameter discrete grey prediction model (FTDGM (1, 1) model) is introduced. Firstly, the data are preprocessed by buffer operators, and then, the FTDGM (1, 1) model is established. In this paper, the parameter estimation method and the specific process of model establishment are presented. Finally, the models of energy consumption in China are built. The advantages and prediction accuracy of the model established in this paper are analyzed, and the data in the following years are effectively predicted, so as to provide theoretical support for the government to formulate reasonable energy policies.
Highlights
Grey system theory is a small sample modeling method proposed by Professor Deng Julong in 1982, which mainly includes grey prediction theory, grey correlation theory, grey decision theory, grey clustering theory, and grey game theory [1, 2]
Many scholars have carried out extensive research studies on the grey prediction model [4,5,6,7,8,9,10,11,12,13,14,15,16,17], whose achievements have played a positive role in improving the grey prediction theory. e GM (1, 1) model requires the transformation of differential equation and difference equation, which will lead to systematic errors
Xie and Liu constructed the DGM (1, 1) model and its extended form. e DGM (1, 1) model does not require the conversion of differential equation and difference equation, but directly uses the difference equation for parameter estimation and model solution, so as to effectively reduce the error source within the model [18]. e GM (1, 1) and DGM (1, 1) models construct prediction models by accumulating quasi-exponential rules of sequences
Summary
Grey system theory is a small sample modeling method proposed by Professor Deng Julong in 1982, which mainly includes grey prediction theory, grey correlation theory, grey decision theory, grey clustering theory, and grey game theory [1, 2]. Zhang and Liu proposed a discrete grey prediction model with linear time-varying parameters and discussed the properties of the model and the parameter solving method, and the model has a completely error-free simulation accuracy for sequences with linear laws and exponential laws [19]. Is paper proposes a discrete grey prediction model based on the weakening buffer operator and fractional order accumulation of linear time-varying parameters. Get β1 (1.00, 1.27 and β2 2.51, 3.58, 6.46, 9.94, 14.24, the simulation 19.61, 26.34), sequence and the average relative error changes to 10.38% It can be seen from the above results that, for an integer order accumulation at the DGM (1, 1) model, the change of the original value will not influence the modeling results of the sequence, which means that the first value has not been effective utilized, which is a serious waste for small sample modeling. Model. e same conclusion can be reached for other grey prediction models
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