Multi-phase information aggregation and dynamic synthetic evaluation based on grey inspiriting control lines. Issue 2 (29th July 2014)

• Record Type: Journal Article
• Authors: Guo, San-dang; Liu, Sifeng; Fang, Zhigeng; Wang, Lingling
• Editors: Naiming Xie, Dr Yingjie Yang and Dr Chuanmin Mi, Professor
• Is Part Of: Grey systems. Volume 4:Issue 2(2014)
• Page Start: 154
• Page End: 163
• Publication Date: 2014-07-29
• Subjects: GM(1, 1) model -- Grey inspiriting control lines -- Dynamic synthetic evaluation -- Information aggregation; Cybernetics -- Periodicals; Systems engineering -- Periodicals; 003.5
• DOI: 10.1108/GS-08-2013-0017
• Languages: English
• ISSNs: 2043-9377

Abstract

Abstract : Purpose: – The purpose of this paper is to put forward a multi-stage information aggregation method based on grey inspiriting control lines to evaluate the objects dynamically and comprehensively. Design/methodology/approach: – According to the evaluation value of the objects, the positive and negative incentive lines were set up and the predicted values were solved based on the grey GM (1, 1) model, so the value with expected information could be evaluated. In the evaluation, the part above the positive incentive line should be "rewarded" and that below the negative incentive line should be "punished" appropriately. Thereby the double incentive effects of "the current development situation and future development trend" to objects could be implemented on the basis of control. Findings: – This method can primarily describe the decision maker's expectancy of the development of evaluation objects and make the evaluation results have better practical application value. Research limitations/implications: – Many comprehensive evaluations were always based on the past information. However, the future development trend of the evaluated object is also very important. This study can be used in the evaluation for future application and development. Originality/value: – The paper succeeds in providing not only a method of multi-phase information aggregation with expectancy information, but also a simple and convenient method solving nonlinear inspiring lines objectively.