A Novel Prediction Model for Sales Forecasting Based on Grey System

2016 ◽  
Author(s):  
Jingmin Wei ◽  
Jia Zhu ◽  
Changqin Huang ◽  
Yong Tang ◽  
Xueqin Lin ◽  
...  
Keyword(s):  
Prediction Model ◽  
Grey System

Wind Speed Prediction Based on Improved Grey Neural Network Model

2014 ◽  
Vol 548-549 ◽  
pp. 1235-1240
Author(s):  
Bin Zeng ◽  
Jian Xiao Zou ◽  
Kai Li ◽  
Xiao Shuai Xin
Keyword(s):  
Neural Network ◽  
Wind Speed ◽  
Prediction Model ◽  
Data Storage ◽  
Wind Farm ◽  
Grey System Theory ◽  
Grey System ◽  
Wind Speed Prediction ◽  
Neural Network Prediction ◽  
Speed Prediction

Wind speed forecasting is an effective method to improve power stability of wind farm. Grey system theory have certain advantages in the study of poor information and uncertainty problems, it is suitable for the system with limited computing power and data storage capacity, such as wind turbine control system. In order to further improve the prediction accuracy of grey model, we combined GM (1, 1) model and BP neural network prediction model in this paper, and improved the combined model by background value optimizing and introducing genetic algorithm. Through analyzing the simulation results and comparing the forecasting results with the actual wind speed, it is clear that the improved combined prediction model is superior to pure grey forecasting model and it meets the needs of the wind power control.

scholarly journals Application of a Fractional Grey Prediction Model Based on a Filtering Algorithm in Image Processing

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Mingyu Tong ◽  
Kailiang Shao ◽  
Xilin Luo ◽  
Huiming Duan
Keyword(s):  
Image Processing ◽  
Prediction Model ◽  
Grey System Theory ◽  
Grey Prediction ◽  
Grey System ◽  
Middle Point ◽  
Filtering Algorithm ◽  
Grey Correlation ◽  
Grey Prediction Model ◽  
Model Based

Image filtering can change or enhance an image by emphasizing or removing certain features of the image. An image is a system in which some information is known and some information is unknown. Grey system theory is an important method for dealing with this kind of system, and grey correlation analysis and grey prediction modeling are important components of this method. In this paper, a fractional grey prediction model based on a filtering algorithm by combining a grey correlation model and a fractional prediction model is proposed. In this model, first, noise points are identified by comparing the grey correlation and the threshold value of each pixel in the filter window, and then, through the resolution coefficient of the important factor in image processing, a variety of grey correlation methods are compared. Second, the image noise points are used as the original sequence by the filter pane. The grey level of the middle point is predicted by the values of the surrounding pixel points combined with the fractional prediction model, replacing the original noise value to effectively eliminate the noise. Finally, an empirical analysis shows that the PSNR and MSE of the new model are approximately 27 and 140, respectively; these values are better than those of the comparison models and achieve good processing effects.

scholarly journals Main Driving Factors and Prediction Model of Total Health Expenditure in China: A Study Based on Grey System Theory

2019 ◽  
Author(s):  
Huanhuan Jia ◽  
Xihe Yu ◽  
Jianxing Yu ◽  
Zhou Zheng ◽  
Yingying Li ◽  
...  
Keyword(s):  
System Theory ◽  
Prediction Model ◽  
Health Expenditure ◽  
The Elderly ◽  
Grey System Theory ◽  
Driving Factors ◽  
System Reform ◽  
Total Health Expenditure ◽  
Grey System ◽  
Correlation Degree

Abstract Background: The continuous increase in total health expenditure has become a social issue of common concern in most countries. In China, the total health expenditure still maintains a fast growth trend which is much higher than the growth of the country’s economy, although the new health system reform had been going on for 8 years until 2017. The aims of the current study were thus to investigate the main driving factors affecting total health expenditure and to establish a prediction model. Methods: Gray system theory was employed to explore the correlation degree between total health expenditure and 13 hot spots from the fields of economy, population, health service utilization, and public policy using national data in China from 2009 to 2017. Besides, a prediction model was established using the main driving factors among the 13 hot spots. Results: The main driving factors related to the changes of total health expenditure were public policy (ranked first), health development, economics, and aging, which correlation degrees were more than 0.7. The average error of the GM(1,7) model was 3.17%, the correlation degree, β , between the predicted simulation sequence and the original sequence was 0.78, the variance ratio, C, was 0.138, and the probability of residuals, P, was 1.0000. Therefore, the prediction model of total health expenditure with 6 main driving factors was excellent. Conclusion: The paper finds that since the new health system reform in China, government policies and social invest have contributed greatly to reducing the burden of health expenditure. However, the development of economic and the increase in the elderly population, which are main driving factors, will increase the total health expenditure, so improving the efficiency of investment and providing the precautionary health care and nursing for the elderly are crucial. Besides, the grey system theory had a good application in the field of health economics and policy.

Development of Acoustical Prediction Model for Asphalt Pavements Using Grey System Approach

2010 ◽  
Vol 11 (3) ◽  
pp. 783-805
Author(s):  
Chia-Ming Wu ◽  
Cheng-chao Lee ◽  
Jia-Chong Lee ◽  
Der-Hsien Shen
Keyword(s):  
Prediction Model ◽  
System Approach ◽  
Asphalt Pavements ◽  
Grey System

Grey Prediction on Sheared Edge Quality in Precision Blanking Process for Micro IT Parts

2011 ◽  
Vol 266 ◽  
pp. 122-125
Author(s):  
Bo Wang ◽  
Jing Bo Chen
Keyword(s):  
Prediction Model ◽  
Product Quality ◽  
Grey Prediction ◽  
Grey System ◽  
Time Increment ◽  
Sheared Edge ◽  
Edge Quality ◽  
Burr Width ◽  
Blanking Process

Sheared edge quality of micro IT parts is an important standard to evaluate product quality. In this paper, a prediction model of sheared edge quality based on grey prediction is studied. By mapping the stroke and the burr width to be the time increment and the eigenvalue of grey system, the grey prediction model was established. The dynamic regularity of burr in actual production was attained from the precision blanking experiment and the prediction of burr width was performed. The results show that the model can predict burr width accurately and needs less sampling data. Thus, it is fit for the requirement of manufacturing.

scholarly journals Optimizing the Grey GM(1,N) Model by Rebuilding All the Back Ground Values

2014 ◽  
Vol 2 (6) ◽  
pp. 543-552
Author(s):  
Xin Ma ◽  
Zhibin Liu ◽  
Yishen Chen
Keyword(s):  
Prediction Model ◽  
Large Error ◽  
Grey System ◽  
Simulation Test ◽  
New Models ◽  
Back Ground

Abstract The GM(1,N) model is a very important prediction model of the grey system. But the inherent defect of GM(1,N), which may cause very large error, is still there. This paper analyzes the source of the error of GM(1,N) and reveals that it’s all the back ground values that effect the precision and applicability of GM(1,N). Three methods are employed to revise the GM(1,N) model. The simulation test shows the new models perform with higher precision and robustness. Even in some extreme cases, in which the original GM(1,N) is invalid, the new models are still valid and perform well.

Research on Duration Prediction of the Coupled Task Set Based on the Grey System Theory

2012 ◽  
Vol 220-223 ◽  
pp. 169-173
Author(s):  
Peng Jia ◽  
Qi Gao ◽  
Rong Zhen Xu ◽  
Xiao Chen Zheng ◽  
Gang Liu
Keyword(s):  
System Theory ◽  
Prediction Model ◽  
Grey System Theory ◽  
Small Sample ◽  
Practical Application ◽  
Grey System ◽  
Task Set ◽  
Posterior Variance ◽  
Duration Prediction

In order to solve the problem of duration predicting in the project with poor information, small sample and uncertainty, a method based on grey system theory is put forward to predicting the duration of the coupled task set. A grey duration prediction model GM(1,1) is built, and the accuracy of the model is tested through residual, degree of incidence and posterior variance. Finally, the feasibility of the prediction model is verified by a practical application case.

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