scholarly journals Prediction on Average Price of Commercial Housing in Sichuan Province and Analysis of Influencing Factors Based on Grey System Theory

2020 ◽  
Author(s):  
Jiaying Li ◽  
Enchi Liang ◽  
Huaxue Zhuang ◽  
Cheng Liu
Keyword(s):  
System Theory ◽  
Influencing Factors ◽  
Sichuan Province ◽  
Grey System Theory ◽  
Average Price ◽  
Grey System ◽  
Commercial Housing

Equipment maintainability and its influencing factors analysis based on grey system theory

2012 ◽  
Vol 2 (3) ◽  
pp. 427-436 ◽  
Author(s):  
Hong‐fa Ke ◽  
Hong‐Mei Du ◽  
Ke He ◽  
Xiao‐Hong Yu
Keyword(s):  
System Theory ◽  
Influencing Factors ◽  
Grey System Theory ◽  
Grey System ◽  
Factors Analysis

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).

scholarly journals Grey Relational Grade Based Quantitative Analysis of the Factors Influencing the Load Characteristics of A Power Grid

2018 ◽  
Vol 53 ◽  
pp. 01012 ◽  
Author(s):  
Wei Pan ◽  
Caijia Lei ◽  
Wei Jia ◽  
Hui Gao ◽  
Binghua Fang
Keyword(s):  
Quantitative Analysis ◽  
Influencing Factors ◽  
Power Grid ◽  
Grey System Theory ◽  
Grey System ◽  
Factors Affecting ◽  
Grey Relational Grade ◽  
Load Characteristics ◽  
Grey Relational ◽  
Main Factor

Regarding analysis of load characteristics of a power grid, there are multiple factors that influence the variation of load characteristics. Among these factors, the influence of different ones on the change of load characteristic is somewhat different, thus the degree of influence of various factors needs to be quantified to distinguish the main and minor factors of load characteristics. Based on this, the grey relational analysis in the grey system theory is employed as the basis of mathematical model in this paper. Firstly, the main factors affecting the load characteristics of a power grid are analysed. Then, the principle of quantitative analysis of the influencing factors by using grey relational grade is introduced. Lastly, the load of Guangzhou power grid is selected as the research object, thereby the main factor of temperature affecting the load characteristics is quantitatively analysed, such that the correlation between temperature and load is established. In this paper, by investigating the influencing factors and the degree of influence of load characteristics, the law of load characteristics changes can be effectively revealed, which is of great significance for power system planning and dispatching operation.

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

Grey-based model for forecasting Mauritius international tourism from different regions

2017 ◽  
Vol 7 (2) ◽  
pp. 259-271 ◽  
Author(s):  
Medha Pirthee
Keyword(s):  
System Theory ◽  
Grey System Theory ◽  
International Tourism ◽  
Grey System ◽  
Private Companies ◽  
Content Type ◽  
System Models ◽  
Economic Decision Making ◽  
Tourism Sector ◽  
The Government

Purpose The purpose of this paper is to understand the trend and forecast the number of tourists from different regions of the world to Mauritius. Design/methodology/approach The paper adopts two grey system models, the even model GM(1,1) and the non-homogeneous discrete grey model (NDGM), to forecast the total number of international tourism to Mauritius and its structure from different regions tourist arrivals to Mauritius for the next three years. Grey system theory models were used to account for uncertainties and the dynamism of the tourism sector environment. The two models were applied as a comparison to obtain more reliable forecasting figures. Findings The results demonstrate that both of the grey system models can be successfully applied with high accuracy for Mauritian tourism prediction, and also the number of tourist arrivals to Mauritius shows a continued augmentation for the upcoming years. Practical implications Forecasting is meaningful since the Government of Mauritius, private companies or any concerned authority can adopt the forecasting methods exposed in this paper for the development of the tourism sector through managerial and economic decision making. Originality/value Mauritius is a charming travel destination. Through this paper, it can be seen that future tourism travel to Mauritius has been successfully predicted based on previous data. Moreover, it seems that the grey system theory models have not been utilised yet as forecasting tools for the tourism sector of Mauritius as opposed to other countries such as China and Taiwan.

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