Study on distance measuring and sorting method of general grey number

2017 ◽  
Vol 7 (3) ◽  
pp. 320-328 ◽  
Author(s):  
Shi-quan Jiang ◽  
Si-feng Liu ◽  
Zhi-geng Fang ◽  
Zhong-xia Liu
Keyword(s):  
Difficult Problem ◽  
Grey System Theory ◽  
Grey System ◽  
Sorting Method ◽  
Content Type ◽  
Source Distance ◽  
Grey Differential Equation ◽  
Grey Number ◽  
Set Up ◽  
Distance Measuring

Purpose The purpose of this paper is to study distance measuring and sorting method of general grey number. Design/methodology/approach First, the concept of generalised grey number based on grey system theory is given in this paper. Second, from the perspective of kernel and degree of greyness of general grey number, the method of measuring the distance of general grey number and its properties are given. At the same time, the concepts of the kernel expectation and the kernel variance of the general grey number are proposed. Findings Up to now, the method of measuring the distance and sorting of general grey number is established. Thus, the difficult problem for set up sorting of general grey number has been solved to a certain degree. Research limitations/implications The method exposed in this paper can be used to integrate information form a different source. Distance measuring and sorting method of general grey number could be extended to the case of grey algebraic equation, grey differential equation and grey matrix which includes general grey numbers, etc. Originality/value The concepts of the kernel expectation and the kernel variance of the general grey number are proposed for the first time in this paper; the novel sorting rules of general grey numbers were also constructed.

First price sealed-bid auction of the grey game improvement model via double-parameter Bayesian estimation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fei Deng ◽  
Sifeng Liu ◽  
Zhigeng Fang
Keyword(s):  
Bayesian Estimation ◽  
Historical Data ◽  
Classical Model ◽  
Grey System Theory ◽  
Grey System ◽  
Content Type ◽  
Sealed Bid ◽  
Grey Number ◽  
Improved Model ◽  
Specific Implementation

PurposeThe improved classical model makes it possible that the evaluation strategy has an optimal tendency, which reveals the purpose of this paper is to facilitate the first price sealed-bid auction more in line with the actual situation. To be more specific, there are several merits in the improvement process. On the one hand, the bid-winning probability can be improved for the bidder; on the other hand, the real market value of the subject matter can be more clearly recognized for the employer.Design/methodology/approachBayesian estimation and grey system theory are referenced in this paper, with the use of double-parameter estimation, little historical data and expert experience. Specific implementation steps are as follows: first of all, using the double-parameter Bayesian estimation to correct the actual valuation of the bid matter v, then introducing the threat factor grey number R in the auction model, giving the improving of the optimal grey quotation and grey expectation utility under the two-party game and finally taking the aerospace component procurement as an example, simulating the bidding process of the bidding parties to arrive at the optimal bid strategy.FindingsThe improved model shows that the optimal strategy will change with the threat factor rather than a fixed value. When the threat factor grey number R follows [0.4, 0.6], the optimal quotation strategy will appear, which means quotation is higher than 50% of the bid matter's valuation.Practical implicationsThe improved model proposed in this paper can strengthen the cost control in the Chinese commercial space process and optimize the pricing strategy for the final launch.Originality/valueThe modified model changes the habit that the bidder's valuation of the bid subject to mainly come from experience and to prompt the model for making full use of little historical data on the foundation of the former. It can reduce the subjective judgment error in the game results; finally, the practical cases are simulated in MATLAB at the same time, and the simulation effect is good, so we can get some more realistic conclusions on this basis.

Algorithm rules of interval grey numbers based on different “kernel” and the degree of greyness of grey numbers

2017 ◽  
Vol 7 (2) ◽  
pp. 168-178 ◽  
Author(s):  
San-dang Guo ◽  
Sifeng Liu ◽  
Zhigeng Fang
Keyword(s):  
Grey System Theory ◽  
Ranking Method ◽  
Relative Degree ◽  
Grey System ◽  
Content Type ◽  
Grey Number ◽  
Definition Of ◽  
Further Development ◽  
Moderate Measure ◽  
Universe Of Discourse

Purpose The purpose of this paper is to establish the algorithm rules of the interval grey numbers and propose a new ranking method of the interval grey numbers. Design/methodology/approach The definitions of “kernels” based on lower measure, upper measure or moderate measure are given according to the properties of the interval grey number problems. By means of the measurement error, the concept of the absolute degree of greyness and the relative degree of greyness corresponding to different “kernel” are given, and different simplified forms of the interval grey numbers are put forward. Findings The definitions of “kernel” and the degree of greyness in this paper not only take the upper limit, lower limit and the coverage of the interval grey numbers into account, but also avoid the inconsistency of the degree of greyness caused by the different universe of discourse. Research limitations/implications Though the method proposed in this paper has some deficiencies, such as the definition of relative degree of greyness is meaningless when the kernel of the interval grey number is 0, it provides a new idea for calculating and sorting the interval grey numbers and is conducive to the further development of the grey system theory. Originality/value The method proposed in this paper can not only distinguish interval grey numbers in different situations, but also avoid the inconsistency of the degree of greyness caused by the different universe of discourse. In this basis, the interval grey number algorithm is established and a new ranking method of interval grey numbers is given.

Natural disaster forecast on the base of townships collaborative emergency

2015 ◽  
Vol 5 (3) ◽  
pp. 392-409 ◽  
Author(s):  
Honglian Guo ◽  
Yunxian Hou ◽  
Baohong Yang ◽  
Hongping Du ◽  
Weiqun Xiao
Keyword(s):  
Natural Disaster ◽  
Cost Reduction ◽  
Forecast Model ◽  
Grey System Theory ◽  
Forecast Errors ◽  
Grey System ◽  
Accuracy Rate ◽  
Content Type ◽  
Set Up ◽  
Emergency Resource

Purpose – The purpose of this paper is to upgrade the collaborative emergency ability of government in the tier of towns, realizing emergency resource share, emergency cost reduction and emergency efficiency improving. This paper mainly aims to solve the problem of forecasting the natural disaster happening year of every township collaborative region in Fangshan District. Design/methodology/approach – First, classify the townships into five collaborative regions through grey clustering. Second, set up a grey disaster forecast model for the whole Fangshan District according the annals of disaster from 1985 to 2012, and forecast the disaster grade. Third, build a grey disaster forecast model for the collaborative regions after constructing the buffer operators of catastrophic sequence according the annals of disaster from 1949 to 2012. Findings – The authors forecasted the happening year and flood grade of future disaster for the whole Fangshan District. The accurate degrees of both flood and drought year model are greater than 90 per cent. The accurate degree of insects calamity year is a little low, but the relative errors are all lower than 3 per cent in recent continuous three times, so in the whole, it can be used. For the collaborative regions, the authors forecasted the future disaster years of them. The accuracy rate of every model is greater than 90 per cent. The result shows that the forecast errors are acceptable. Research limitations/implications – In the models, for the purpose of good accuracy, the authors used different initial data. For example, in the forecast model for whole Fangshan District disaster year, the authors used the data from 1985 to 2012, while in the forecast model for the disaster grade of it, the authors used the data from 1949 to 2012. In the disaster year forecast model for collaborative region, the authors also used the data from 1949 to 2012. If the authors can find a model that has high accuracy rate by using all the date information, it will be better. Practical implications – Township is the most basic level of government organization in China, researching on collaborative emergency in township will do help to take targeted precautions measures against calamity according to the characteristic there. At the same time realizing emergency cost reduction and emergency efficiency improving based on the advantages of emergency resource share, short rescue distance, little effects of communication destruction. Social implications – Because of the stochastic occurring of disasters, it is very important to forecast the happening time of disasters accurately. This paper forecasted the natural disaster happening time of Fangshan District through grey catastrophic model, aimed at giving decision support to related department and strengthen the disaster prevention power targetedly. Originality/value – It is well known that the greater the system, the steadier it is, and the easier to forecast it. Fangshan District, Beijing, is a medium-sized and small system in regional research, while townships are small systems. It is rarely a big challenge for the authors to forecast the disaster years in Fangshan and its collaborative townships. In this paper, the authors used grey system model and Markov transfer matrix in forecasting the disaster years and the disaster grade of flood in Fangshan District. All of them are new trying to using grey system theory in disaster forecast for Fangshan District, Beijing.

General grey number decision-making model and its application based on intuitionistic grey number set

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shi Quan Jiang ◽  
SiFeng Liu ◽  
ZhongXia Liu
Keyword(s):  
Decision Model ◽  
Prediction Models ◽  
Distance Measure ◽  
Measuring Method ◽  
Difficult Problem ◽  
Grey Prediction ◽  
Content Type ◽  
Grey Number ◽  
Set Up ◽  
Incidence Analysis

PurposeThe purpose of this paper is to study the grey decision model and distance measuring method of general grey number.Design/methodology/approachFirst, intuitionistic grey number (IGN) set and an IGN are defined by grey number probability function. Second, each interval grey number in general grey number is represented by an IGN and converts the general grey number into an IGN set. Final, the operation of two general grey numbers is defined as the operation between IGN sets, and the distance measure of the general grey number is given.FindingsUp to now, the method of measuring the distance and the grey decision model of general grey number is established. Thus, the difficult problem for set up decision mode of general grey number has been solved to a certain degree.Research limitations/implicationsThe method exposed in this paper can be used to integrate information form a different source. The method that a general grey number converted to a set of IGNs could be extended to the case of grey incidence analysis models, grey prediction models and grey clustering evaluation models, which includes general grey numbers, etc.Originality/valueThe concepts of IGN and IGN set are proposed for the first time in this paper; The operation of two general grey numbers can be defined as the operation between IGN sets. On this basis, the algorithm of IGN, the integration operator of IGN and the distance measure between IGN sets are given.

Explanations about grey information and framework of grey system modeling

2017 ◽  
Vol 7 (2) ◽  
pp. 179-193 ◽  
Author(s):  
Naiming Xie
Keyword(s):  
System Modeling ◽  
Evolutionary Process ◽  
Grey System Theory ◽  
Limited Data ◽  
Grey System ◽  
Content Type ◽  
System Models ◽  
Different Types ◽  
Grey Number ◽  
Uncertainty Models

Purpose The purpose of this paper is to summarize the different types of grey information, explain the mechanism of grey system modeling and reconstruct the framework of grey system theory (GST). Design/methodology/approach GST has been developed for more than three decades; however, the framework of GST is still in an evolutionary process. This manuscript first explains grey information in detail, and then summarizes a series of grey system models under limited data and poor information. Figures and general steps for different types of grey system models are provided in this paper. Findings The findings in this paper clearly differentiate between grey information and other uncertainty information. The differences between grey system models and other uncertainty models are clearly explained. In addition, general steps for different grey system models are given which demonstrate the orientation of grey system modeling. Practical implications Theoretical framework is very important for developing a new theory. This paper clarified grey information and grey system-based modeling mechanism. It is very useful to understand and explain the systematic framework of GST and it contributes undoubtedly to make GST perfect. Originality/value Grey information is explained in terms of limited data and two types of grey numbers. Accordingly, all of the grey system models were divided into limited data-based grey system models and grey number-based grey system models.

An uncertain pure linguistic approach on evaluation of enterprise integrity based on grey information

2016 ◽  
Vol 6 (3) ◽  
pp. 353-364 ◽  
Author(s):  
Zhen Zhen Ma ◽  
Jianjun Zhu
Keyword(s):  
Ideal Point ◽  
Grey System Theory ◽  
Decision Makers ◽  
Fuzzy Evaluation ◽  
Grey System ◽  
Content Type ◽  
Grey Relational Grade ◽  
Grey Number ◽  
Linguistic Approach ◽  
Grey Relational

Purpose Currently, for the evaluation of enterprise credit, many specific values of indexes are difficult to obtain, so decision makers tend to give a form of uncertain linguistic variable. To solve this kind of problem, the purpose of this paper is to introduce an uncertain pure linguistic approach on evaluation of enterprise integrity based on grey information. Design/methodology/approach Initial uncertain linguistic variables given by experts are transferred into interval grey numbers, and their greyness of degree is computed. Then, the greyness of degree is applied to adjust the weights of experts. Moreover, the core of each interval grey number is calculated, and through giving the positive ideal point and negative ideal point, which are binary numbers, the comprehensive grey relational grade between the linguistic number and the two points is calculated, respectively, as well to get the ranking result of projects by considering both core and greyness of degree. Findings The model is applied to a case, and the result verifies the validity and practicability of the model which reveals high effectiveness. Practical implications This model provides a new feasible method in a growing number of fuzzy evaluation schemes in the fields of enterprise integrity and contributes to getting better and more accurate results. Originality/value In this paper, the greyness of degree is introduced to the model to adjust the experts’ weights, and it reflects the thought of “making full use of the information” in grey system theory and further enriches the system of grey decision-making theory as well as expanding its application scope.

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.

Evaluation of outpatient satisfaction and service quality of Pakistani healthcare projects

2018 ◽  
Vol 8 (4) ◽  
pp. 462-480 ◽  
Author(s):  
Saad Ahmed Javed ◽  
Sifeng Liu
Keyword(s):  
Service Quality ◽  
Private Sector ◽  
Healthcare Delivery ◽  
Grey System Theory ◽  
Public Healthcare ◽  
Grey System ◽  
Healthcare Delivery System ◽  
Public And Private ◽  
Content Type ◽  
The Public

PurposeThe purpose of this paper is to analyse the relationship between outpatient satisfaction and the five constructs of healthcare projects’ service quality in Pakistan using Deng’s grey incidence analysis (GIA) model, absolute degree GIA model (ADGIA), a novel second synthetic degree GIA (SSDGIA) model and two approaches of decision-making under uncertainty.Design/methodology/approachThe study proposes a new synthetic GIA model and demonstrates its feasibility on data (N=221) collected from both public and private sector healthcare projects of Punjab, the most populous province of Pakistan, using a self-administered questionnaire developed using the original SERVQUAL approach.FindingsThe results of decision analysis approach indicated that outpatients’ satisfaction from the private sector healthcare projects is higher as compared to the public healthcare projects’. The results from the proposed model revealed that tangibility and reliability play an important role in shaping the patient satisfaction in the public and private sectors, respectively.Originality/valueThe study is pioneer in evaluating a healthcare system’s service quality using grey system theory. The study proposes the SSDGIA model as a novel method to evaluate parameters comprehensively based on their mutual association (given by absolute degree of grey incidence) and inter-dependencies (given by Deng’s degree of grey incidence), and tests the new model in the given scenario. The study is novel in terms of its analysis of data and modelling. The study also proposes a comprehensive structure of the healthcare delivery system of Pakistan.

Identifying key industry factors of remanufacturing industry using grey incidence analysis

2016 ◽  
Vol 6 (3) ◽  
pp. 398-414 ◽  
Author(s):  
Wenjie Liu ◽  
Jing Zhang ◽  
Chenfan Wu ◽  
Xiangyun Chang
Keyword(s):  
Grey System Theory ◽  
Grey System ◽  
Annual Sale ◽  
Content Type ◽  
Building Area ◽  
Industry Characteristic ◽  
Grey Incidence Analysis ◽  
Incidence Analysis ◽  
Practical Implications ◽  
Key Industry

Purpose The purpose of this paper is to identify most favorable (or quasi-preferred) industry characteristics of remanufacturing industry and most favorable (or quasi-preferred) industry factors which have an effect on these characteristics so as to improve these factors. Design/methodology/approach Grey system theory has prominent advantage of using few data and uncertainty information to analyze many factors. Therefore, it is more suited for system analysis than traditional statistical analysis methods like regression analysis, variance analysis and principal component analysis, which require massive data, certain probability distribution in the data and few variant factors. So in this paper, grey incidence analysis method, which is an important part of grey system theory, is used to identify industry characteristics and key industry factor of remanufacturing industry in China and then put forward appropriate industrial policies and countermeasures to improve these industry factors. Findings According to the results of this study, it reveals that there are no most favorable industry characteristics and no most favorable industry factors in remanufacturing industry of China. “Annual sale of remanufacturing industry” is identified as quasi-preferred industry characteristic, and “total number of employees with master degree or above in remanufacturing enterprise” is identified as the quasi-preferred industry factor. “Total building area of remanufacturing enterprise” is referred as the most unfavorable industry factors. Practical implications Judging from the findings of this study, four practical implications are summarized as follows: “annual sale of remanufacturing industry” should be given great importance because it is a quasi-preferred industry characteristic. “Total number of employees with master degree or above in remanufacturing enterprise” and “total number of research institution and university participated in remanufacturing” should be further strengthened by establishing an industry-university-research institute collaboration network, due to the fact that they are the top two quasi-preferred industry factors. “Total investment of remanufacturing industry” and “total annual R&D expenditures” have not played their due role in improving remanufacturing industry, so they should be moderately controlled so as to reduce waste of investment. “Total building area of remanufacturing enterprise” must be strictly controlled because of its little impact on remanufacturing industry. Originality/value In this research, grey incidence analysis is applied to identify key industry factors of remanufacturing industry for the first time. It helps in finding industry factors which are in urgent need of improvement and assists in making appropriate industrial policies and countermeasures to improve them by studying relationships between industry characteristic and industry factors.

A grey rough set model for evaluation and selection of software cost estimation methods

2014 ◽  
Vol 4 (1) ◽  
pp. 3-12 ◽  
Author(s):  
Jun Liu ◽  
Jian-Zhong Qiao
Keyword(s):  
System Theory ◽  
Rough Set ◽  
Cost Estimation ◽  
Estimation Method ◽  
Grey System Theory ◽  
Estimation Methods ◽  
Software Cost Estimation ◽  
Grey System ◽  
Software Cost ◽  
Content Type

Purpose – Due to the limitation of acknowledgment, the complexity of software system and the interference of noises, this paper aims to solve the traditional problem: traditional software cost estimation methods face the challenge of poor and uncertain inputs. Design/methodology/approach – Under such circumstances, different cost estimation methods vary greatly on estimation accuracy and effectiveness. Therefore, it is crucial to perform evaluation and selection on estimation methods against a poor information database. This paper presents a grey rough set model by introducing grey system theory into rough set based analysis, aiming for a better choice of software cost estimation method on accuracy and effectiveness. Findings – The results are very encouraging in the sense of comparison among four machine learning techniques and thus indicate it an effective approach to evaluate software cost estimation method where insufficient information is provided. Practical implications – Based on the grey rough set model, the decision targets can be classified approximately. Furthermore, the grey of information and the limitation of cognition can be overcome during the use of the grey rough interval correlation cluster method. Originality/value – This paper proposed the grey rough set model combining grey system theory with rough set for software cost estimation method evaluation and selection.

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