A decision-making mechanism of network risk control based on grey relation

The aim of this chapter is to develop a hybrid decision-making framework for studying the risk issues related to failure of an industrial system. On the basis of plant expert's knowledge, failure mode effect analysis (FMEA) sheet has been generated and various failure causes associated with the sub-systems were listed. On the basis of three risk factors, namely probability of occurrence of failure, severity and non-detection (, and ), Risk Priority Numbers (RPN) for each failure cause has been tabulated. The demerits of FMEA approach in prioritizing the failure causes has been overcome by implementing fuzzy rule-based tool. The consistency and heftiness of the ranking results have been tested by implementing grey relation analysis (GRA) approach. Comparison of ranking results has been done for effective decision making of ranking results. The accuracy of decision results would be highly useful in developing a planned maintenance policy for the plant. The proposed framework has been tested with its application on a cooling tower system of a thermal power plant located in the northern part of India.

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Decision-Making of Irrigation Scheme for Soybeans in the Huaibei Plain Based on Grey Entropy Weight and Grey Relation–Projection Pursuit

Entropy ◽

10.3390/e21090877 ◽

2019 ◽

Vol 21 (9) ◽

pp. 877 ◽

Cited By ~ 1

Author(s):

Yi Cui ◽

Shangming Jiang ◽

Juliang Jin ◽

Ping Feng ◽

Shaowei Ning

Keyword(s):

Decision Making ◽

Water Consumption ◽

Projection Pursuit ◽

Crop Water ◽

Irrigation Scheme ◽

Entropy Weight ◽

Entropy Weight Method ◽

Weight Method ◽

Projection Pursuit Model ◽

Grey Relation

To provide a scientific reference for formulating an effective soybean irrigation schedule in the Huaibei Plain, potted water deficit experiments with nine alternative irrigation schemes during the 2015 and 2016 seasons were conducted. An irrigation scheme decision-making index system was established from the aspects of crop water consumption, crop growth process and crop water use efficiency. Moreover, a grey entropy weight method and a grey relation–projection pursuit model were proposed to calculate the weight of each decision-making index. Then, nine alternative schemes were sorted according to the comprehensive grey relation degree of each scheme in the two seasons. The results showed that, when using the entropy weight method or projection pursuit model to determine index weight, it was more direct and effective to obtain the corresponding entropy value or projection eigenvalue according to the sequence of the actual study object. The decision-making results from the perspective of actual soybean growth responses at each stage for various irrigation schemes were mostly consistent in 2015 and 2016. Specifically, for an integrated target of lower water consumption and stable biomass yields, the scheme with moderate-deficit irrigation at the soybean branching stage or seedling stage and adequate irrigation at the flowering-podding and seed filling stages is relatively optimal.

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

Grey Systems Theory and Application ◽

10.1108/gs-10-2018-0049 ◽

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.

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