TY - JOUR
T1 - Fuzzy risk analysis by similarity-based multi-criteria approach to classify alternatives
AU - Nikfalazar, Sanaz
AU - Akbarzadeh Khorshidi, Hadi
AU - Hamadani, Ali Zeinal
PY - 2016/9/1
Y1 - 2016/9/1
N2 - In this paper, a new method for fuzzy risk analysis based on similarity of fuzzy numbers is presented. First of all, the similarity-based multi-criteria approach is used to find the similarity between generalized trapezoidal fuzzy numbers and the desired fuzzy number to rank them. The geometry distance, spread difference, perimeter ratio, area ratio, and height ratio have been considered as criteria. Secondly, the proposed ranking approach is used for fuzzy risk analysis. Severity of loss, probability of failure, and failure ignorance possibility are the parameters to assess the risk of various alternatives. In the proposed fuzzy risk analysis, the alternatives can be classified into different levels in terms of their risk. Therefore, fuzzy risk analysis leads to classification and prioritization of the alternatives. Finally, a numerical example is presented to illustrate the applicability of the proposed method.
AB - In this paper, a new method for fuzzy risk analysis based on similarity of fuzzy numbers is presented. First of all, the similarity-based multi-criteria approach is used to find the similarity between generalized trapezoidal fuzzy numbers and the desired fuzzy number to rank them. The geometry distance, spread difference, perimeter ratio, area ratio, and height ratio have been considered as criteria. Secondly, the proposed ranking approach is used for fuzzy risk analysis. Severity of loss, probability of failure, and failure ignorance possibility are the parameters to assess the risk of various alternatives. In the proposed fuzzy risk analysis, the alternatives can be classified into different levels in terms of their risk. Therefore, fuzzy risk analysis leads to classification and prioritization of the alternatives. Finally, a numerical example is presented to illustrate the applicability of the proposed method.
KW - Data mining
KW - Fuzzy risk analysis
KW - Generalized trapezoidal fuzzy numbers
KW - Linguistic terms
KW - Similarity-based multi-criteria
UR - http://www.scopus.com/inward/record.url?scp=84983070763&partnerID=8YFLogxK
U2 - 10.1007/s13198-016-0414-6
DO - 10.1007/s13198-016-0414-6
M3 - Article
AN - SCOPUS:84983070763
SN - 0975-6809
VL - 7
SP - 250
EP - 256
JO - International Journal of Systems Assurance Engineering and Management
JF - International Journal of Systems Assurance Engineering and Management
IS - 3
ER -