Risk Assessment for Ships Based on Information Entropy and Intuitionistic Fuzzy Linguistic Variables

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Junzhong Bao ◽  
Xizhao Wang ◽  
Zixuan Yu ◽  
Yong Wang
Keyword(s):  
Risk Assessment ◽  
Information Entropy ◽  
Linguistic Variables ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Linguistic

Intuitionistic Fuzzy Linguistic Induced Ordered Weighted Averaging Operator for Group Decision Making

2015 ◽  
Vol 23 (04) ◽  
pp. 627-648 ◽  
Author(s):  
Sidong Xian ◽  
Wenting Xue ◽  
Jianfeng Zhang ◽  
Yubo Yin ◽  
Qin Xie
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Weighted Averaging ◽  
Linguistic Variables ◽  
Attribute Weights ◽  
Intuitionistic Fuzzy ◽  
Operational Laws ◽  
Multiple Attribute ◽  
Fuzzy Linguistic

With respect to multiple attribute group decision making (MAGDM) problems, in which the attribute weights take the form of real numbers, and the attribute values take the form of intuitionistic fuzzy linguistic variables, a decision analysis approach is proposed. In this paper, we develop an intuitionistic fuzzy linguistic induce OWA (IFLIOWA) operator and analyze the properties of it by utilizing some operational laws of intuitionistic fuzzy linguistic variables. A new method based on the IFLIOWA operator for multiple attribute group decision making (MAGDM) is presented. Finally, a numerical example is used to illustrate the applicability and effectiveness of the proposed method.

scholarly journals Risk Assessment using Fuzzy Linguistic Variables in Korean

2015 ◽  
Vol 30 (4) ◽  
pp. 151-158 ◽  
Author(s):  
Hyeon-Kyo Lim ◽  
Sanghun Byun ◽  
Hyunjung Kim
Keyword(s):  
Risk Assessment ◽  
Linguistic Variables ◽  
Fuzzy Linguistic

Risk analysis of cutting system under intuitionistic fuzzy environment

2020 ◽  
Vol 1 (1) ◽  
pp. 162-173
Author(s):  
Dinesh Kumar Kushwaha ◽  
◽  
Dilbagh Panchal ◽  
Anish Sachdeva ◽  
◽  
...  
Keyword(s):  
Risk Assessment ◽  
Failure Mode ◽  
Thermal Power ◽  
Failure Detection ◽  
Engineering System ◽  
Effect Analysis ◽  
Intuitionistic Fuzzy ◽  
Mode Effect ◽  
Cutting System ◽  
Failure Mode Effect Analysis

Failure Mode Effect Analysis (FMEA) is popular and versatile approach applicable to risk assessment and safety improvement of a repairable engineering system. This method encompasses various fields such as manufacturing, healthcare, paper mill, thermal power industry, software industry, services, security etc. in terms of its application. In general, FMEA is based on Risk Priority Number (RPN) score which is found by product of probability of Occurrence (O), Severity of failure (S) and Failure Detection (D). As human judgement is approximate in nature, the accuracy of data obtained from FMEA members depend on degree of subjectivity. The subjective knowledge of members not only contains uncertainty but hesitation too which in turn, affect the results. Fuzzy FMEA considers uncertainty and vagueness of the data/ information obtained from experts. In order to take into account, the hesitation of experts and vague concept, in the present work we propose integrated framework based on Intuitionistic Fuzzy- Failure Mode Effect Analysis (IF-FMEA) and IF-Technique for Order Preference by Similarity to Ideal Solution (IF-TOPSIS) techniques to rank the listed failure causes. Failure cause Fibrizer (FR) was found to be the most critical failure cause with RPN score 0.500. IF-TOPSIS has been implemented within IF-FMEA to compare and verify ranking results obtained by both the IF based approaches. The proposed method was presented with its application for examining the risk assessment of cutting system in sugar mill industry situated in western Uttar Pradesh province of India. The result would be useful for the plant maintenance manager to fix the best maintenance schedule for improving availability of cutting system.

scholarly journals Fire Risk Assessment in Healthcare Settings: Application of FMEA Combined with Multi‐Criteria Decision Making Methods

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Fateme Omidvari ◽  
Mehdi Jahangiri ◽  
Reza Mehryar ◽  
Moslem Alimohammadlou ◽  
Mojtaba Kamalinia
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Fire Risk ◽  
Fire Detection ◽  
Healthcare Setting ◽  
Multi Criteria Decision Making ◽  
Intuitionistic Fuzzy ◽  
Healthcare Settings ◽  
Fire Risk Assessment ◽  
Risk Parameters

Fire is one of the most dangerous phenomena causing major casualties and financial losses in hospitals and healthcare settings. In order to prevent and control the fire sources, first risk assessment should be conducted. Failure Mode and Effect Analysis (FMEA) is one of the techniques widely used for risk assessment. However, Risk Priority Number (RPN) in this technique does not take into account the weight of the risk parameters. In addition, indirect relationships between risk parameters and expert opinions are not considered in decision making in this method. The aim is to conduct fire risk assessment of healthcare setting using the application of FMEA combined with Multi‐Criteria Decision Making (MCDM) methods. First, a review of previous studies on fire risk assessment was conducted and existing rules were identified. Then, the factors influencing fire risk were classified according to FMEA criteria. In the next step, weights of fire risk criteria and subcriteria were determined using Intuitionistic Fuzzy Multiplicative Best-Worst Method (IFMBWM) and different wards of the hospital were ranked using Interval-Valued Intuitionistic Fuzzy Combinative Distance-based Assessment (IVIFCODAS) method. Finally, a case study was performed in one of the hospitals of Shiraz University of Medical Sciences. In this study, fire alarm system (0.4995), electrical equipment and installations (0.277), and flammable materials (0.1065) had the highest weight, respectively. The hospital powerhouse also had the highest fire risk, due to the lack of fire extinguishers, alarms and fire detection, facilities located in the basement floor, boilers and explosive sensitivity, insufficient access, and housekeeping. The use of MCDM methods in combination with the FMEA method assesses the risk of fire in hospitals and health centers with great accuracy.

Fuzzy Matter-Element Evaluation Method for Analysis of Debris Flow Risk Assessment

2012 ◽  
Vol 446-449 ◽  
pp. 3058-3061 ◽  
Author(s):  
Chun Tan ◽  
Jian Ping Chen ◽  
Yu Zhen Pan ◽  
Cen Cen Niu ◽  
Li Ming Xu
Keyword(s):  
Risk Assessment ◽  
Debris Flow ◽  
Information Entropy ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Practical Application ◽  
Element Analysis ◽  
Matter Element Analysis ◽  
Concept Of Information

Based on the principle of fuzzy matter-element analysis, the concept of information entropy is introduced to establish a fuzzy matter-element evaluation method. This method is utilized to comprehensively evaluate the degree of debris flow. The classifications of debris flow are regarded as the objects of matter-element and their indexes for evaluation as well as the corresponding fuzzy values are used to construct the composite fuzzy matter-elements. By calculating the relevancy the comprehensive evaluation of debris flow can be carried out. This model is applied to analyze the degree of debris flow in the practical application. The application shows that the model is effective and practical.

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