Mohammad Hossein Basiri
Tarbiat Modares University
13 Papers
45 Citations
Mohammad Hossein Basiri is an academic researcher from Tarbiat Modares University. The author has contributed to research in topics: SWOT analysis & Computer science. The author has an hindex of 6, co-authored 9 publications. Previous affiliations of Mohammad Hossein Basiri include Shahid Beheshti University.
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Papers
Ranking the strategies of mining sector through anp and topsis in a swot framework
Reza Azimi,Abdolreza Yazdani-Chamzini,Mohammad Majid Fouladgar,Edmundas Kazimieras Zavadskas,Mohammad Hossein Basiri +4 more
TL;DR: An integrated model for prioritizing the strategies of Iranian mining sector is proposed using the SWOT analysis to assign feasible strategies, ANP was applied in order to obtain the weight of SWOT factors, and the strategies were ranked through TOPSIS technique.
An ANP–SWOT approach for interdependency analysis and prioritizing the Iran׳s steel scrap industry strategies
TL;DR: In this article, the authors designed a model and implemented the efficient strategic factors (Strengths, Weaknesses, Opportunities and Threats), via the SWOT analysis, the appropriated strategies, SO, ST, WO and WT are determined.
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Risk Analysis for Critical Infrastructures Using Fuzzy TOPSIS
TL;DR: The fuzzy TOPSIS as a fuzzy multi criteria decision making technique is adopted to determine the weights of each criterion and the importance of alternatives with respect to criteria and the proposed model demonstrates a significant improvement in comparison with conventional RAMCAP.
Risk assessment of critical asset using fuzzy inference system
TL;DR: Fuzzy RAMCAP is introduced in order to extend RAMCAP and a case study is presented to show the effectiveness and the capability of the new risk analysis model.
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Developing a new model based on neuro-fuzzy system for predicting roof fall in coal mines
Mohammad Farid,Mehdi Mohamadi HosseinAbadi,Abdolreza Yazdani-Chamzini,Siamak Haji Yakhchali,Mohammad Hossein Basiri +4 more
TL;DR: This paper demonstrates that prediction of roof fall rate by the ANFIS model is satisfactory and uses the subtractive clustering method to generate fuzzy rules based on 109 data of roof performance from US coal mines.
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