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Author

Wen-bin Lv

Bio: Wen-bin Lv is an academic researcher. The author has contributed to research in topics: Business & Analytic network process. The author has co-authored 1 publications.

Papers
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Proceedings ArticleDOI
29 Nov 2010
TL;DR: In this paper, an EPC project risk evaluation model is constructed based on ANP (Analytic Network Process) -Fuzzy Comprehensive Evaluation to evaluate the integrated risk level and hypermatrix is utilized to compute and determine the weight of all the indexes.
Abstract: In order to assess and analyze the importance of the elements which have a significant impact on the risk, analytic network process is applied to establish the network structure model of risk evaluation index system for EPC project. And hypermatrix is utilized to compute and determine the weight of all the indexes. An EPC project risk evaluation model is constructed based on ANP (Analytic Network Process) -Fuzzy Comprehensive Evaluation to evaluate the integrated risk level. Validity of such EPC project risk evaluation model would be proved by a demonstration case analysis with help of Super Decision software. Results are shown at the last part of this paper.
Journal ArticleDOI
TL;DR: In this article , a dea-based financial refinement management effectiveness evaluation method is proposed aiming at the low fitting degree of the traditional financial management performance evaluation method, a DEA-based fin-cial refinement management approach is proposed.
Abstract: Aiming at the low fitting degree of the traditional financial management performance evaluation method, a dea-based financial refinement management effectiveness evaluation method is proposed. This paper analyzes the overall structure of the financial department, takes the effectiveness evaluation index of financial management at home and abroad as the reference object, and constructs the effectiveness evaluation index system of financial fine management. According to the evaluation index system, CR model and BCC model in DEA method are adopted to evaluate the efficiency of financial delicacy management. Experimental results show that the method has small error, high fitting index and good practical performance.