Drought grade assessment method based on grey cloud incidence clustering model

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dang Luo ◽  
Yan Hu ◽  
Decai Sun
Keyword(s):  
Decision Making ◽  
Cloud Model ◽  
Henan Province ◽  
Maximum Deviation ◽  
Content Type ◽  
Risk Levels ◽  
Clustering Model ◽  
Subjective Weight ◽  
Drought Disaster ◽  
Grey Number

PurposeThe purpose of this paper is to establish a grey cloud incidence clustering model to assess the drought disaster degree under 15 indexes in 18 cities of Henan province.Design/methodology/approachThe grey incidence degree between each index and ideal index is used to determine the index weight and combined with the subjective weight, the comprehensive weight is given; the traditional possibility function is transformed into grey cloud possibility function by using the principle of maximum deviation and maximum entropy, which fully reflects the coexistence of multiple decision-making conclusions and constructs the grey cloud incidence clustering model.FindingsThe drought disaster degree of Henan province is divided into four grades under the selected 15 indexes. The drought grades show obvious regional differences. The risk levels of the east and southwest are higher, and the risk levels of the north and southeast are lower. This result is consistent with the study of drought disaster grades in Henan province, which shows the practicability and usefulness of the model.Practical implicationsIt provides an effective method for the assessment of drought disaster grade and the basis for formulating disaster prevention and mitigation plan.Originality/valueBy studying the method of multiattribute and multistage decision-making with interval grey number information. The objective weight model of index value is designed, and the subjective weight is given by experts. On the basis of the two, the comprehensive weight of subjective and objective combination is proposed, which effectively weakens the randomness of subjective weight and reasonably reflects the practicality of index decision-making. The time weight reflects the dynamic of the index. The traditional possibility function is transformed into the grey cloud possibility function, which effectively takes advantage of the grey cloud model in dealing with the coexistence of fuzzy information, grey information and random information. Thus, the conflict between the decision-making results and the objective reality is effectively solved. The interval grey number can make full use of the effective information and improve the accuracy of the actual information.

Grey clustering model based on kernel and information field

2019 ◽  
Vol 10 (1) ◽  
pp. 56-67 ◽  
Author(s):  
Dang Luo ◽  
Zhang Huihui
Keyword(s):  
Weight Function ◽  
Fuzzy Clustering ◽  
Theoretical Basis ◽  
Disaster Risk ◽  
Content Type ◽  
Clustering Model ◽  
Grey Clustering ◽  
Drought Disaster ◽  
Regional Drought ◽  
Grey Number

Purpose The purpose of this paper is to propose a grey clustering model based on kernel and information field to deal with the situation in which both the observation values and the turning points of the whitenization weight function are interval grey numbers. Design/methodology/approach First, the “unreduced axiom of degree of greyness” was expanded to obtain the inference of “information field not-reducing”. Then, based on the theoretical basis of inference, the expression of whitenization weight function with interval grey number was provided. The grey clustering model and fuzzy clustering model were compared to analyse the relationship and difference between the two models. Finally, the paper model and the fuzzy clustering model were applied to the example analysis, and the interval grey number clustering model was established to analyse the influencing factors of regional drought disaster risk in Henan Province. Findings The example analysis results illustrate that although the two clustering methods have different theoretical basis, they are suitable for dealing with complex systems with uncertainty or grey characteristic, solving the problem of incomplete system information, which has certain feasibility and rationality. The clustering results of case study show that five influencing factors of regional drought disaster risk in Henan Province are divided into three classes, consistent with the actual situation, and they show the validity and practicability of the clustering model. Originality/value The paper proposes a new whitenization weight function with interval grey number that can transform interval grey number operations into real number operations. It not only simplifies the calculation steps, but it has a great significance for the “small data sets and poor information” grey system and has a universal applicability.

A comparative analysis of grey ranking approaches

2019 ◽  
Vol 9 (4) ◽  
pp. 472-487 ◽  
Author(s):  
Davood Darvishi ◽  
Jeffrey Forrest ◽  
Sifeng Liu
Keyword(s):  
Decision Making ◽  
Comparative Analysis ◽  
Partial Order ◽  
Design Methodology ◽  
Total Order ◽  
Interval Numbers ◽  
Content Type ◽  
Important Decision ◽  
Grey Number ◽  
Order Kernel

Purpose Ranking and comparing grey numbers represent a very important decision-making procedure in any given grey environment. The purpose of this paper is to study the existing approaches of ordering interval grey numbers in the context of decision making by surveying existing definitions. Design/methodology/approach Different methods developed for comparing grey numbers are presented along with their disadvantages and advantages in terms of comparison outcomes. Practical examples are employed to show the importance and necessity of using appropriate methods to compare grey numbers. Findings Most the available methods are not suitable for pointing out which number is larger when the nuclei of the grey numbers of concern are the same. Also, these available methods are also considered in terms of partial order and total order. Kernel and degree of greyness of grey numbers method is more advantageous than other methods and almost eliminates the shortcomings of other methods. Originality/value Different methods for ranking grey numbers are presented where each of them has disadvantages and advantages. By using different methods, grey interval numbers are compared and the results show that some methods cannot make grey number comparisons in some situations. The authors intend to find a method that can compare grey numbers in any situation. The findings of this research can prevent errors that may occur based on inaccurate comparisons of grey numbers in decision making. There are various research studies on the comparison of grey numbers, but there is no research on the comparison of these methods and their disadvantages, advantages or their total or partial order.

Crowdsourcing the ecosystem’s expectations: a decision-making process to manage the unmanageable

2014 ◽  
Vol 42 (3) ◽  
pp. 3-8 ◽  
Author(s):  
Haydn Shaughnessy
Keyword(s):  
Decision Making ◽  
Ecosystem Change ◽  
Content Type ◽  
Risk Levels ◽  
Continuous Innovation ◽  
Uncertainty Monitoring ◽  
Traditional Sense ◽  
High Level ◽  
Wealth Generation ◽  
A Company

Purpose – The author warns that nowadays a company must learn to be “co-productive” with an app developer community, a supplier community, a content community, an advocacy community or a customer ecosystem in order to stay competitive through continuous innovation. Leaders need new tools to promote informed decisions. Design/methodology/approach – The article shows how companies monitoring dynamic ecosystem change can develop crowd-based reporting scorecards to guide decision making. Findings – Increasingly it is the innovations and expertise of the ecosystem, not the talents and resources of the firm, that are crucial to its future wealth generation. But many of the consequences of ecosystem change are, in fact, unmanageable in any traditional sense. An experimental way to identify the uncertainty produced by a dynamic ecosystem offers decision support. Practical implications – The uncertainty monitoring experiments described in this article can clarify the risk levels and the need for preparatory investments. They offer a high level view of the dynamics of the new market ecosystem environment. Originality/value – This article offers cutting-edge insights for managers struggling to make decisions about investments related to the dynamic ecosystem of users, suppliers, partners and customers in their companies’ markets.

An enhanced algorithm for calculating the degree of greyness of interval grey numbers and its application

Kybernetes ◽  
2019 ◽  
Vol 49 (6) ◽  
pp. 1721-1740
Author(s):  
Shuaishuai Geng ◽  
Yu Feng ◽  
Yaoguo Dang ◽  
Junjie Wang ◽  
Rizwan Rasheed
Keyword(s):  
Decision Making ◽  
Design Methodology ◽  
Decision Making Process ◽  
Content Type ◽  
Operational Mechanism ◽  
Operation Process ◽  
Algebraic Operations ◽  
Grey Number ◽  
Operation Results ◽  
Selection Of

Purpose This paper aims to propose an enhanced algorithm and used to decision-making that specifically focuses on the choice of a domain in the calculation of degree of greyness according to the principle of grey numbers operation. The domain means the emerging background of interval grey numbers, it is vital for the operational mechanism of such interval grey numbers. However, the criteria of selection of domain always remain same that is not only for the calculated grey numbers but also for the resultant grey numbers, which can be assumed as unrealistic up to a certain extent. Design/methodology/approach The existence of interval grey number operation based on kernel and the degree of greyness containing two calculation aspects, which are kernel and the degree of greyness. For the degree of greyness, it includes concepts of domain and calculation of the domain. The concepts of a domain are defined. The enhanced algorithm is also comprised of four deductive theorems and eight rules that are linked to the properties of the enhanced algorithm of the interval grey numbers based on the kernel and the degree of greyness. Findings Aiming to improve the algorithm of the degree of greyness for interval grey numbers, based on the variation of domain in the operation process, the degree of greyness of the operation result is defined in this paper, and the specific expressions for algebraic operations are given, which is relevant to the kernel, the degree of greyness and the domain. Then, these expressions are used to the algorithm of interval grey numbers based on the kernel and the degree of greyness, improving the accuracy of the operation results. Originality/value The enhanced algorithm in this paper can effectively reduce the loss of information in the operation process, so as to avoid the situation where the decision values are the same and scientific decisions cannot be made during the grey evaluation and decision-making process.

Grey relational decision making model of three-parameter interval grey number based on AHP and DEA

2019 ◽  
Vol 10 (1) ◽  
pp. 25-37
Author(s):  
Bingjun Li ◽  
Xiaoxiao Zhu
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Agriculture Industry ◽  
Parameter Interval ◽  
Grey Number ◽  
Index Weight ◽  
Decision Making Model ◽  
Grey Relational ◽  
Grey Relation

Purpose The purpose of this paper is to put forward the grey relational decision-making model of three-parameter interval grey number based on Analytic Hierarchy Process (AHP) and Data Envelopment Analysis (DEA), based on the previous study of grey relational decision-making model, and it considers the advantages of the decision-making schemes and the subjective preferences of decision makers. Design/methodology/approach First of all, through AHP, the preference of each index is analyzed and the index weight is determined. Second, the DEA model is adopted to obtain the index weight from the perspective of the most beneficial to each scheme and objectively reflect the advantages of different schemes. Then, assign the comprehensive weights to each index of the grey relational decision-making model of three-parameter interval grey number, and calculate the grey relation degree of each scheme to rank the schemes. Findings The effectiveness of the model is proved by an example of carrier aircraft selection. Practical implications The applicability of this model is analyzed by taking carrier aircraft selection as an example. In fact, this model can also be widely used in agriculture, industry, economy, society and other fields. Originality/value In this paper, the combination of AHP and DEA is used to determine the index weight. Based on which, the grey relation degree under the three-parameter interval grey number is calculated. It intended the application space of the grey relational decision-making model.

A self-testing cloud model for multi-criteria group decision making

2016 ◽  
Vol 33 (6) ◽  
pp. 1767-1783 ◽  
Author(s):  
Ting-Cheng Chang ◽  
Hui Wang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Cloud Model ◽  
New Approach ◽  
Content Type ◽  
Qualitative And Quantitative ◽  
Composite Scale ◽  
Self Testing

Purpose – The purpose of this paper is to select the best scaling coefficient during the quantitative-qualitative conversion. Design/methodology/approach – Cloud model can describe the qualitative concept of randomness and fuzziness, achieve uncertain transition between qualitative and quantitative in the field of multi-criteria group decision and has been receiving widespread attention. This paper discusses scale conversion issues of the cloud model when evaluating qualitative information. In order to improve the accuracy of the evaluation on multi-attribute decision problems based on uncertainty of natural linguistic information, this paper proposes a method of self-testing cloud model based on a composite scale (with the exponential scale and the scale as a basis). Findings – Through experimental verification results show that under composite scale, the best suitable selection of can effectively improve the accuracy and reliability of decision results. Originality/value – This research presents a new approach to determine the suitable value for coefficient based on uncertain knowledge of natural multi-criteria group decision making, and gives concrete steps and examples. This method has positive significance to improve the quality of qualitative and quantitative conversion based on cloud model.

Grey target decision-making model of interval grey number based on cone volume

2017 ◽  
Vol 7 (2) ◽  
pp. 247-258 ◽  
Author(s):  
Lizhen Wang ◽  
Wuyong Qian
Keyword(s):  
Decision Making ◽  
Entropy Method ◽  
Maximal Entropy ◽  
Information Distortion ◽  
Content Type ◽  
Model Based ◽  
Proposed Model ◽  
Grey Number ◽  
Decision Making Model ◽  
The Impact

Purpose The purpose of this paper is to propose a grey target decision model based on cobweb area in order to overcome the effect and influence from the extreme value of the index on the decision result. However, it does not take into account the impact of the correlation between indicators on the angle of the index, and produce a certain degree decision information distortion as a result of the equal angle between the indicators. In order to solve the above problems, a novel grey decision-making model based on cone volume is proposed. Design/methodology/approach In this paper, the model uses the whitening weight function to whiten the interval grey number, and the Delphi method and the maximal entropy method are exploited to integrate the weight of the index. On the basis of this, the center of the bull’s eye, the weight and the index value are constructed as the center circle, the radius, and the high cone, respectively. The scheme is selected by the volume of the cone, the decision is made according to the order relation, and the example is utilized to prove and analyze the validity of the proposed model. Findings The results show that the proposed model can well improve the traditional grey target decision-making model from the modeling object and modeling method. Practical implications The method exposed in the paper can be used to deal with the grey target decision-making problems which characteristics are multi-indexes, and the attribute values are interval grey numbers. Originality/value The paper succeeds in overcoming the disadvantages of grey target decision making based on the target center distance and the cobweb area.

Multi-attribute grey target decision method with three-parameter interval grey number

2016 ◽  
Vol 6 (2) ◽  
pp. 270-280 ◽  
Author(s):  
Ye Li ◽  
Shanli Zhu ◽  
San-dang Guo
Keyword(s):  
Decision Making ◽  
Distance Measure ◽  
Ranking Method ◽  
Content Type ◽  
Uncertain Environment ◽  
Decision Method ◽  
Multi Attribute Decision Making ◽  
Parameter Interval ◽  
Grey Number ◽  
Bull's Eye

Purpose – The purpose of this paper is to propose the grey target decision method based on three-parameter interval grey number for dealing with multi-attribute decision-making problems under uncertain environment. Design/methodology/approach – First, the kernel and ranking method of three-parameter interval grey number are defined, which is the basis of determining the positive and negative bull’s-eye. Next, a new distance measure of three-parameter interval grey number is defined in view of the importance of the “center of gravity” point. Furthermore, a new comprehensive bull’s-eye distance is proposed based on the kernel which integrates the distance between different attributes to the positive and negative bull’s-eye. Then attribute weights are obtained by comprehensive bull’s-eye distance minimum and grey entropy maximization. Findings – The paper provides a grey target decision method based on three-parameter interval grey number and example analysis shows that the method proposed in this paper is more reasonable and effective. Research limitations/implications – If we have a better understanding of the distribution characteristics of three-parameter interval grey number, it is possible to have a more reasonable measure of the distance of three-parameter interval grey number. Practical implications – The paper provides a grey target decision method, which can help decision maker deal with multi-attribute decision-making problems under uncertain environment. Originality/value – This paper proposed the kernel and ranking method of three-parameter interval grey number, and defined a new distance measure of three-parameter interval grey number and proposed a new comprehensive bull’s-eye distance, Furthermore, this paper structured a grey target decision method based on three-parameter interval grey number.

Dynamic multi-attribute decision-making method with three-parameter interval grey number based on the prospect theory

2018 ◽  
Vol 8 (4) ◽  
pp. 424-435 ◽  
Author(s):  
Ye Li ◽  
Dongxing Zhang
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Value Function ◽  
Reference Points ◽  
Content Type ◽  
Time Points ◽  
Decision Method ◽  
Multi Attribute Decision Making ◽  
Parameter Interval ◽  
Grey Number

Purpose The purpose of this paper is to propose a dynamic multi-attribute decision-making method based on the prospect theory for dealing with the dynamic multi-attribute decision-making problem with three-parameter interval grey number. Design/methodology/approach First, the kernel and comparison rule of three-parameter interval grey numbers are defined, which are the basis of collecting and sorting grey numbers. Next, the prospect value function is determined in view of the decision-making information with different time points as the reference points. Then, an optimal model for solving the attribute weight and time weight is constructed based on the grey entropy principle. Findings The paper provides a dynamic grey interrelation decision method based on the prospect theory with three-parameter interval grey number, and the example analysis shows that the method proposed in this paper has validity and rationality. Research limitations/implications If we have a better understanding of the weights of different reference points, it is possible to receive a more reasonable expression for the comprehensive prospect utility value function. Practical implications The paper provides a grey interrelation decision method based on the prospect theory, which can help the decision maker deal with the dynamic multi-attribute decision-making problems under the uncertain environment. Originality/value The paper proposes the kernel and ranking method of three-parameter interval grey number, and uses different time points as the reference points to define the prospect value function. Furthermore, this paper structures a dynamic grey interrelation decision method with three-parameter interval grey number based on the prospect theory.

Study on urbanization process evaluation and provincial comparison

2014 ◽  
Vol 4 (1) ◽  
pp. 13-23
Author(s):  
Ye Li ◽  
Meng Qin
Keyword(s):  
Henan Province ◽  
Evaluation Index System ◽  
Cluster Method ◽  
General Level ◽  
Clear Understanding ◽  
Urbanization Process ◽  
Urbanization Level ◽  
Content Type ◽  
Clustering Model ◽  
Fixed Weight

Purpose – This paper aims to evaluate the stage and level of Henan province urbanization and provide basis for decision making. Design/methodology/approach – At first, build the evaluation index system which includes 17 indexes in four classes so that can reflect the level of urbanization development of the entire region comprehensively. Then build the gray clustering model based on set pair. On this basis, the paper evaluates the urbanization process in Henan province. In order to get a clear understanding of the urbanization level in Henan province, the paper selects several typical provinces and compares them with Henan province in urbanization process. Findings – The results show that the urbanization level in Henan province belongs to the general level; there is a gap in urbanization process between Henan province and other advanced provinces. Practical implications – The paper put forward a method to evaluate the urbanization process in Henan province and get a clear understanding of the urbanization level in Henan province. Originality/value – The paper combines the set pair analysis and the gray fixed weight cluster method based on triangular whiten weight function, which can avoid the defect that the assessment result is too vague and the difference is not significant.

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