Research of Accidents due to Human Factor in Coal Mine Based on GM Model

2015 ◽  
Vol 1092-1093 ◽  
pp. 692-695 ◽  
Author(s):  
Shang Quan Ma ◽  
Jing Fu
Keyword(s):  
System Theory ◽  
Incomplete Information ◽  
Coal Mine ◽  
Human Factor ◽  
Grey System Theory ◽  
Forecasting Model ◽  
Grey System ◽  
Forecasting Models ◽  
Grey Forecasting ◽  
Development Tendency

Grey forecast can master the developing law of system through dealing with incomplete information of system at present. On the basis of actual data of Feng Feng Coal Mine, the grey forecasting model for coal mine accidents due to human factor in Feng Feng by using the grey system theory in this paper, it is shown that models which are built have good precisions. Safety and production of Feng Feng Coal Mine are forecasted by using grey forecasting models which are built. The results show that the forecasting models will help coal mines to forecast accidents due to human factor next year and generally tally with development tendency of Feng Feng Coal Mine.

Study on the second grey relational grade and its properties

Kybernetes ◽  
2010 ◽  
Vol 39 (8) ◽  
pp. 1330-1335 ◽  
Author(s):  
Yan Ma
Keyword(s):  
System Theory ◽  
Design Methodology ◽  
Grey System Theory ◽  
Forecasting Model ◽  
Grey System ◽  
Content Type ◽  
Grey Forecasting ◽  
Grey Relational Grade ◽  
Grey Relational ◽  
Practical Implications

PurposeThe purpose of this paper is to propose a second relational grade based on the general grey relational grade and analyze several of its properties.Design/methodology/approachGrey system theory. The paper proposes and studies second grey relational grade, establishes second grey relational formula, and studies several characteristics of second grey relational formula.FindingsProposing a second relational grade proved it could solve the problem of the parallelism partly and weaken relativity of space position.Research limitations/implicationsUntil now, the problem of the consistency could not be solved, nor could the problem of the effect which keeps the sequence the same.Practical implicationsThe precision of the grey forecasting model could be strengthened if used in the forecasting model.Originality/valueThe general relational grade only thinks over the relation between two sequences but does not involve the relation in one sequence. The second relational grade considers these two, so if the forecasting model is established with it, the model should be more exact.

scholarly journals Explanation of terms of grey forecasting models

2017 ◽  
Vol 7 (1) ◽  
pp. 123-128 ◽  
Author(s):  
Sifeng Liu ◽  
Yingjie Yang
Keyword(s):  
System Theory ◽  
Design Methodology ◽  
Grey System Theory ◽  
Grey System ◽  
Content Type ◽  
Forecasting Models ◽  
Grey Forecasting ◽  
Key Terms ◽  
Practical Implications

Purpose The purpose of this paper is to present the terms of grey forecasting models and techniques. Design/methodology/approach The definitions of basic terms about grey forecasting models and techniques are presented one by one. Findings The reader could know the basic explanation about the important terms about various grey forecasting models and techniques from this paper. Practical implications Many of the authors’ colleagues thought that unified definitions of key terms would be beneficial for both the readers and the authors. Originality/value It is a fundamental work to standardise all the definitions of terms for a new discipline. It is also propitious to spread and universal of grey system theory.

Durability Prediction of Asphalt Mixture under Freeze-Thaw Cycle Based on GM (1,N) Grey Model

2015 ◽  
Vol 744-746 ◽  
pp. 1244-1248 ◽  
Author(s):  
Rui Xiong ◽  
Lu Wang
Keyword(s):  
System Theory ◽  
Asphalt Mixture ◽  
Grey System Theory ◽  
Grey System ◽  
Freeze Thaw ◽  
Splitting Strength ◽  
Grey Forecasting ◽  
Thaw Cycle ◽  
Freeze Thaw Cycle ◽  
Durability Prediction

In order to predict the durability of asphalt mixture under freeze-thaw cycles, the porosity and splitting strength of asphalt mixture under freeze-thaw cycle are studied, and GM(1, N) model in grey system theory is established. The results show that there is a good correlation between the porosity and the splitting strength in the durability factors of asphalt mixture. The value of the porosity increases with the increasing of the freeze-thaw times, and the value of the splitting strength decreased with the increasing of the freeze-thaw times. The GM(1, N) grey forecasting model can predict the porosity and the splitting strength well, and the calculated results agree well with the experimental data. Therefore, it is feasible to introduce the grey system theory in the prediction study of the durability of asphalt mixture.

scholarly journals Time-Delayed Polynomial Grey System Model with the Fractional Order Accumulation

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Lin Chen ◽  
Zhibin Liu ◽  
Nannan Ma
Keyword(s):  
System Theory ◽  
Fractional Order ◽  
Grey System Theory ◽  
Small Sample ◽  
System Model ◽  
Grey Prediction ◽  
Grey System ◽  
Forecasting Models ◽  
New Information ◽  
Grey System Model

In this work, a novel time-delayed polynomial grey prediction model with the fractional order accumulation is put forward, which is abbreviated as TDPFOGM(1,1), based on the new grey system theory to predict the small sample in comparison with the existing forecasting models. The new model takes into account the nonhomogeneous term and the priority of new information can be better reflected in the in-sample model. The data in this paper all come from the existing literatures. The results demonstrate that the TDPFOGM(1,1) model outperforms the TDPGM(1,1) and FOGM(1,1) model.

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).

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