Grey system theory-based models in time series prediction

2010 ◽  
Vol 37 (2) ◽  
pp. 1784-1789 ◽  
Author(s):  
Erdal Kayacan ◽  
Baris Ulutas ◽  
Okyay Kaynak
Keyword(s):  
System Theory ◽  
Time Series ◽  
Time Series Prediction ◽  
Grey System Theory ◽  
Grey System

Deformation Prediction Based on Time Series Analysis and Grey System Theory

2011 ◽  
Vol 368-373 ◽  
pp. 2147-2152 ◽  
Author(s):  
Dong Liang Qiao ◽  
Ming Zhao
Keyword(s):  
System Theory ◽  
Time Series ◽  
Time Series Analysis ◽  
Large Deviation ◽  
Original Data ◽  
Grey System Theory ◽  
Grey System ◽  
Deformation Prediction ◽  
Series Analysis

For the long-term monitoring of structure, the deformation trend changes periodically and is hard to extract. A small amount of recent data can be selected to avoid such problem. The study refers to the idea of grey system theory and provides an improved way of deformation prediction in time series analysis with a small amount of data. By cumulating the original data, the trend item is made clear and the rule of data becomes obvious. The prediction results show that the way provided by this article gives a more accurate prediction in the short term. When the prediction results have a large deviation with actual deformation, it can be believed that the trend has changed and the monitored structure may be affected.

AGO-Based Time Series Prediction Method Using LS-SVR

2012 ◽  
Vol 220-223 ◽  
pp. 2133-2137
Author(s):  
Yang Ming Guo ◽  
Xiao Lei Li ◽  
Jie Zhong Ma
Keyword(s):  
Complex System ◽  
Time Series ◽  
Prediction Accuracy ◽  
Time Series Prediction ◽  
Prediction Method ◽  
Health Condition ◽  
Grey System Theory ◽  
Good Prediction ◽  
Grey System ◽  
Complex Dynamic

Fault or health condition prediction of complex system equipments has attracted more and more attention in recent years. Complex system equipments often show complex dynamic behavior and uncertainty, it is difficult to establish precise physical model. Therefore, the time series of complex equipments are often used to implement the prediction in practice. In this paper, in order to improve the prediction accuracy, based on grey system theory, accumulated generating operation (AGO) with raw time series is made to improve the data quality and regularity, and then inverse accumulated generating operation (IAGO) is performed to get the prediction results with the sequence, which is computed by LS-SVR. The results indicate preliminarily that the proposed method is an effective prediction method for its good prediction precision.

Prediction of Technical Reserves Based on Grey Model — GM(1,1): Evidence from Non-life Egyptian Insurance Market

2019 ◽  
Vol 10 (9) ◽  
pp. 852-860
Author(s):  
Mahmoud Elsayed ◽  
◽  
Amr Soliman ◽  
Keyword(s):  
System Theory ◽  
Grey System Theory ◽  
Insurance Market ◽  
Grey Model ◽  
Loss Ratio ◽  
Grey System ◽  
Mathematical Technique ◽  
Supervisory Authority ◽  
Error Ratio ◽  
Using Data

Grey system theory is a mathematical technique used to predict data with known and unknown characteristics. The aim of our research is to forecast the future amount of technical reserves (outstanding claims reserve, loss ratio fluctuations reserve and unearned premiums reserve) up to 2029/2030. This study applies the Grey Model GM(1,1) using data obtained from the Egyptian Financial Supervisory Authority (EFSA) over the period from 2005/2006 to 2015/2016 for non-life Egyptian insurance market. We found that the predicted amounts of outstanding claims reserve and loss ratio fluctuations reserve are highly significant than the unearned premiums reserve according to the value of Posterior Error Ratio (PER).

Application of Grey System Theory to tree growth prediction

2000 ◽  
Vol 11 (1) ◽  
pp. 34-36 ◽  
Author(s):  
Wang Jing ◽  
Hou Yuesong ◽  
Li Weilin ◽  
Cheng Wenhui
Keyword(s):  
System Theory ◽  
Tree Growth ◽  
Grey System Theory ◽  
Grey System ◽  
Growth Prediction
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