Research on Comprehensive Utility Evaluation Model of the Infrastructure ERP System

Li, Zhou; Chen, Ran; Tang, Xuejun; Ke, Fangchao; Liu, Wanfang; Ren, Lei; Zhang, Lingle

doi:10.1109/acpee53904.2022.9783855

Cited by 1 publication

(3 citation statements)

References 3 publications

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“…Recently, there are two main categories of methods for determining weights, qualitative analysis including analytic hierarchy process (AHP) [16][17][18][19] and quantitative analysis including fuzzy cluster analysis 20 , entropy weight method (EWM) [21][22][23] , and index weight determination method based on principal component analysis 24 , etc. Fuzzy clustering is suitable for clustering large-scale data by calculating the uncertainty degree of samples belonging to various categories and performing clustering analysis.…”

Section: Related Workmentioning

confidence: 99%

“…In order to avoid the subjective judgement of a single expert and the clerical error in scoring, it is necessary to give the final evaluation result by the combination of AHP and EWM, which realizes both objective and common sense judgement of weight assignment 25 . The combination of AHP and EWM has been studied in 16 and a comprehensive utility evaluation model was proposed, through AHP to evaluate performance and value, entropy methods to evaluate objective attributes, and combining subjective and objective weights to obtain a final comprehensive utility evaluation weight. In 26 , a combination of subjective and objective weight design scheme based on EMW and AHP was put forward, and the combined weight was optimized by Lagrange multiplier method for the evaluation of body modeling design.…”

Section: Related Workmentioning

confidence: 99%

“…Different from the 16,[26][27][28] that made a comprehensive evaluation weight from the perspective of weighted summation and alternate revision of weight design scheme, in the paper, an evaluation scheme is designed, which combines expert experience as weighting factors, the weighted geometric mean (WGMM) method, and the WLSM to make the evaluation index weight more stable and accurate. In addition, in view of the fact that some dimension indexes may be wrongly marked by multiple experts, this paper designs a scheme to deal with abnormal dimension indexes, which increases the usability of small sample data by automatically correcting abnormal data.…”

Section: Related Workmentioning

confidence: 99%

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Research on evaluation index method of cloud-network convergence capability

Ma,

Chen,

Wang

et al. 2023

Sci Rep

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There is no measurable and evaluable index system for cloud-network convergence that provides guidance and reference for the subsequent construction and development of cloud-network convergence. It is a big project to select and evaluate the indexes of cloud-network convergence, which requires suitable index selection and index evaluation schemes. Based on analytic hierarchy process (AHP) and entropy weight method, this paper proposes an improved AHP (i-AHP) index selection scheme and index evaluation scheme leveraging the years of experts’ experience, the geometric mean and the least square method. The improved weighted least square method (WLSM) is finally proved to be more stable for index evaluation scheme by adding abnormal data. In addition, the index weight obtained by the index evaluation scheme with WLSM are provided as a reference for the future development of cloud-network convergence. The simulation results show that the proposed scheme is superior to the existing index evaluation scheme and can avoid the weight deviation caused by the disturbance and fluctuation of abnormal data.

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