scholarly journals Research on a Novel Kernel Based Grey Prediction Model and Its Applications

2016 ◽  
Vol 2016 ◽  
pp. 1-9
Author(s):  
Xin Ma
Keyword(s):  
Prediction Models ◽  
Kernel Method ◽  
Nonlinear Function ◽  
Grey Model ◽  
Production Data ◽  
World Production ◽  
Grey Prediction ◽  
Gas Well ◽  
Exponential Time ◽  
Well Production

The discrete grey prediction models have attracted considerable interest of research due to its effectiveness to improve the modelling accuracy of the traditional grey prediction models. The autoregressive GM(1,1)model, abbreviated as ARGM(1,1), is a novel discrete grey model which is easy to use and accurate in prediction of approximate nonhomogeneous exponential time series. However, the ARGM(1,1)is essentially a linear model; thus, its applicability is still limited. In this paper a novel kernel based ARGM(1,1)model is proposed, abbreviated as KARGM(1,1). The KARGM(1,1)has a nonlinear function which can be expressed by a kernel function using the kernel method, and its modelling procedures are presented in details. Two case studies of predicting the monthly gas well production are carried out with the real world production data. The results of KARGM(1,1)model are compared to the existing discrete univariate grey prediction models, including ARGM(1,1), NDGM(1,1,k), DGM(1,1), and NGBMOP, and it is shown that the KARGM(1,1)outperforms the other four models.

Analysis of Boundary-Dominated Gas Well Production Data

2019 ◽  
Author(s):  
Shaibu Mohammed ◽  
Prosper Anumah ◽  
Justice Sarkodie-Kyeremeh ◽  
Anthony Morgan ◽  
Emmanuel Acheaw
Keyword(s):  
Production Data ◽  
Gas Well ◽  
Well Production

Applying Grey Forecasting Model on the Milk Yield of Guangxi

2014 ◽  
Vol 556-562 ◽  
pp. 4461-4464
Author(s):  
De Wang Li ◽  
Da Ming Xu ◽  
Wu Sheng Wang
Keyword(s):  
Milk Production ◽  
Prediction Models ◽  
Production Data ◽  
Forecasting Model ◽  
Grey Theory ◽  
Market Demand ◽  
Grey Prediction ◽  
Grey Forecasting ◽  
Livestock Products ◽  
Statistical Yearbook

By using milk production data of Guangxi statistical yearbook from 2001 to 2010, based on the Grey theory and Grey prediction models, which are GM(1,1), have been adopted to predict the milk throughput of Guangxi in this paper. So we establish the GM(1,1) prediction model and predict the milk production of Guangxi from 2011 to 2020. The results show that the Grey theory and Grey prediction models have good simulation and feasibility. At the same time, with the combination of livestock products market demand, we provide livestock enterprises and farmers with some appropriate recommendations.

scholarly journals An Improved Nonequidistant Grey Model Based on Simpson Formula and Its Application

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zhiming Hu ◽  
Chong Liu
Keyword(s):  
Prediction Accuracy ◽  
Prediction Models ◽  
Prediction Performance ◽  
Grey System Theory ◽  
Grey Model ◽  
Grey Prediction ◽  
Grey System ◽  
Proposed Model ◽  
Grey Models ◽  
High Prediction

Grey prediction models have been widely used in various fields of society due to their high prediction accuracy; accordingly, there exists a vast majority of grey models for equidistant sequences; however, limited research is focusing on nonequidistant sequence. The development of nonequidistant grey prediction models is very slow due to their complex modeling mechanism. In order to further expand the grey system theory, a new nonequidistant grey prediction model is established in this paper. To further improve the prediction accuracy of the NEGM (1, 1, t2) model, the background values of the improved nonequidistant grey model are optimized based on Simpson formula, which is abbreviated as INEGM (1, 1, t2). Meanwhile, to verify the validity of the proposed model, this model is applied in two real-world cases in comparison with three other benchmark models, and the modeling results are evaluated through several commonly used indicators. The results of two cases show that the INEGM (1, 1, t2) model has the best prediction performance among these competitive models.

scholarly journals Forecasting Chinese Wind Power Installed Capacity Using a Novel Grey Model with Parameters Combination Optimization

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xiaoshuang Luo ◽  
Bo Zeng ◽  
Hui Li ◽  
Wenhao Zhou
Keyword(s):  
Prediction Model ◽  
Wind Power ◽  
Prediction Models ◽  
Grey Model ◽  
The Novel ◽  
Grey Prediction ◽  
Grey Prediction Model ◽  
Combination Optimization ◽  
Installed Capacity ◽  
Novel Model

The intermittent and uncertain characteristics of wind generation have brought new challenges for the hosting capacity and the integration of large-scale wind power into the power system. Consequently, reasonable forecasting wind power installed capacity (WPIC) is the most effective and applicable solution to meet this challenge. However, the single parameter optimization of the conventional grey model has some limitations in improving its modeling ability. To this end, a novel grey prediction model with parameters combination optimization is proposed in this paper. Firstly, considering the modeling mechanism and process, the order of accumulation generation of the grey prediction model is optimized by Particle Swarm Optimization (PSO) Algorithm. Secondly, as different orders of accumulation generation correspond to different parameter matrixes, the background value coefficient of the grey prediction model is optimized based on the optimal accumulation order. Finally, the novel model of combinational optimization is employed to simulate and forecast Chinese WPIC, and the comprehensive error of the novel model is only 1.34%, which is superior to the other three grey prediction models (2.82%, 1.68%, and 2.60%, respectively). The forecast shows that China’s WPIC will keep growing in the next five years, and some reasonable suggestions are put forward from the standpoint of the practitioners and governments.

scholarly journals A new grey quadratic polynomial model and its application in the COVID-19 in China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jianbo Zhang ◽  
Zeyou Jiang
Keyword(s):  
Prediction Models ◽  
Early Stage ◽  
Quadratic Polynomial ◽  
Grey Model ◽  
Grey Prediction ◽  
New Model ◽  
Polynomial Term ◽  
Death Cases ◽  
Analytical Expressions ◽  
Model Technique

AbstractThis paper develops a new grey prediction model with quadratic polynomial term. Analytical expressions of the time response function and the restored values of the new model are derived by using grey model technique and mathematical tools. With observations of the confirmed cases, the death cases and the recovered cases from COVID-19 in China at the early stage, the proposed forecasting model is developed. The computational results demonstrate that the new model has higher precision than the other existing prediction models, which show the grey model has high accuracy in the forecasting of COVID-19.

Comparison of Two Grey Models Applied in Predicting Numbers of Candidates for College Entrance Examination

2011 ◽  
Vol 105-107 ◽  
pp. 2225-2228
Author(s):  
Gang Li ◽  
Ying Fang ◽  
Ya La Tong
Keyword(s):  
Decision Making ◽  
Prediction Models ◽  
Technical Information ◽  
Grey Model ◽  
Entrance Examination ◽  
Grey Prediction ◽  
College Entrance Examination ◽  
College Entrance ◽  
Grey Models ◽  
The Difference

This paper mainly used two different grey models to predict the numbers of candidates of applying for the college entrance examination. We firstly introduced the conception of GM (1,1,D) and GM (1,1,C), briefly explained the difference between them from the aspect of theory, and then put them into the application of predicting the situation of variance of candidates for college entrance examination. Finally, we analyzed the reasons for this change and countermeasures. Compared to the application of numbers of candidates for college entrance examination by using two grey prediction models, this paper gives an effective method of data analysis, and provides technical information for the relevant decision-making departments. This paper set a good example for the application of selecting the correct grey model to address specific problems.朗读 显示对应的拉丁字符的拼音 字典

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