Method of Group Decision Making with Interval Grey Numbers based on Grey Correlation and Relative Close Degree

With the development of society, big data\u27s concept is mentioned more and more. However, in the numerous and complex mass data, the effective information is often very limited, and the data often show the complex characteristics of "close and orderly short-term correlation and large long-term disturbance", which is difficult to be expressed by a long sequence composed of a single real value. This paper takes the interval grey number as the research object for the uncertain system of "less data and poor information". According to the multi-attribute group decisions problem with attribute’s values of interval grey number and the weights of decision-makers and attributes that are completely unknown, a method of group decision making with interval grey numbers based on grey correlation and relative close degree is proposed. For the purpose of making effective decisions, the weights of decision-makers and attributes are calculated by correlation degree of decision information which is measured by the model of grey correlation analysis based on interval grey number deviation degree. On this basis, the correlation degree between the scheme and the positive and negative ideal schemes are computed, and then the grey correlation and relative close degree of the scheme is calculated. Finally, the scheme is sorted according to the value of the grey correlation and relative close degree. The rationality and feasibility of the proposed method are verified by numerical examples

Grey GERT Network Model of Equipment Lifetime Evaluation Based on Small Samples

The reliability evaluation of high reliability and long life equipment is widely concerned in recent decades. Enough failure samples of these kinds of equipment are not easy or economic to obtain in reliability test, in addition, experience information is sometimes inaccurate or uncertainty. To overcome the deficiency in traditional method which requires large numbers of samples, a quantitative analysis model of equipment reliability evaluation is proposed in this paper in view of the few failure data of equipment life tests. GERT network is introduced to describe the kinds of working states of the equipment system and random process of equipment state transition choice after stress impact of single component. Considering the uncertainty and inaccuracy of the statistical data and experience information, the parameters of GERT network are represented by interval grey number. The system equivalent transfer function could be obtained by GERT matrix solving algorithm, and the reliability evaluation of equipment system can be realized. The case study results show that the equipment reliability evaluation Grey-GERT model based on small samples would save much time with little accuracy losing. Besides, the study provides a new thinking for reliability accelerated life test