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Symmetry 2017, 9(8), 149; doi:10.3390/sym9080149

Evaluating Investment Risks of Metallic Mines Using an Extended TOPSIS Method with Linguistic Neutrosophic Numbers

School of Resources and Safety Engineering, Central South University, Changsha 410083, China
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Received: 26 July 2017 / Revised: 2 August 2017 / Accepted: 3 August 2017 / Published: 8 August 2017
(This article belongs to the Special Issue Neutrosophic Theories Applied in Engineering)
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Abstract

The investment in and development of mineral resources play an important role in the national economy. A good mining project investment can improve economic efficiency and increase social wealth. Faced with the complexity and uncertainty of a mine’s circumstances, there is great significance in evaluating investment risk scientifically. In order to solve practical engineering problems, this paper presents an extended TOPSIS method combined with linguistic neutrosophic numbers (LNNs). Firstly, considering that there are several qualitative risk factors of mining investment projects, the paper describes evaluation information by means of LNNs. The advantage of LNNs is that major original information is reserved with linguistic truth, indeterminacy, and false membership degrees. After that, a number of distance measures are defined. Furthermore, a common status is that the decision makers can’t determine the importance degrees of every risk factor directly for a few reasons. With respect to this situation, the paper offers a weight model based on maximizing deviation to obtain the criteria weight vector objectively. Subsequently, a decision-making approach through improving classical TOPSIS with LNNs comes into being. Next, a case study of the proposed method applied in metallic mining projects investment is given. Some comparison analysis is also submitted. At last, the discussions and conclusions are finished. View Full-Text
Keywords: metallic mine project; investment risks evaluation; linguistic neutrosophic numbers; maximum deviation; extended TOPSIS metallic mine project; investment risks evaluation; linguistic neutrosophic numbers; maximum deviation; extended TOPSIS
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Liang, W.; Zhao, G.; Wu, H. Evaluating Investment Risks of Metallic Mines Using an Extended TOPSIS Method with Linguistic Neutrosophic Numbers. Symmetry 2017, 9, 149.

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