• The Journal of Economics, Marketing and Management
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• v.10 no.5
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• pp.1-6
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• 2022

Purpose: To overcome the question that depends too much on expert's subjective judgment in traditional risk identification, this paper structure the multilevel generalized fuzzy comprehensive evaluation mathematics model of the risk identification of project, to research the risk identification of the project. Research design, data and methodology: This paper constructs the multilevel generalized fuzzy comprehensive evaluation mathematics model. Through iterative algorithm of AHP analysis, make sure the important degree of the sub project in risk analysis, then combine expert's subjective judgment with objective quantitative analysis, and distinguish the risk through identification models. Meanwhile, the concrete method of multilevel generalized fuzzy comprehensive evaluation is probed. Using the index weights to analyse project risks is discussed in detail. Results: The improved fuzzy comprehensive evaluation algorithm is proposed in the paper, at first the method of fuzzy sets core is used to optimize the fuzzy relation matrix. It improves the capability of the algorithm. Then, the method of entropy weight is used to establish weight vectors. This makes the computation process fair and open. And thereby, the uncertainty of the evaluation result brought by the subjectivity can be avoided effectively and the evaluation result becomes more objective and more reasonable. Conclusions: In this paper, we use an improved fuzzy comprehensive evaluation method to evaluate a railroad engineering project risk. It can give a more reliable result for a reference of decision making.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.21
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• pp.29-41
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• 1990

An assessment of risk in industrial and urban environments is essential in the prevention of accident and in the analysis of situations which are hazardous to public health and safety. The risk imposed by a particular hazard increases with the likelihood of occurence of the event, the exposure and the possible consequence of that event. In a traditional approach, the calculation of a quantitative value of risk is usually based on an assignment of numerical values of each of the risk factors. Then the product of the values of likelihood, exposure and consequences called risk score is derived. However vagueness and imprecision in mathematical quantification of risk are equated with fuzziness rather than randomness. In this paper, a fuzzy set theoretic approach to risk analysis is proposed as an alternative to the techniques currently used in the area of systems safety. Then the concept of risk evaluation using linguistic representation of the likelihood, exposure and consequences is introduced. A risk assessment model using approximate reasoning technique based on fuzzy logic is presented to drive fuzzy values of risk and numerical example for risk analysis is also presented to illustrate the results.

• Korean Journal of Construction Engineering and Management
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• v.1 no.1 s.1
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• pp.53-62
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• 2000

This study proposes FREES(Fuzzy Risk Evaluation Expert System) for analyzing and evaluating risks occurring during the construction process. The feasibility of this system model was tested by virtual scenario. For the development of the model, at first, risk breakdown structure was established based on risks identified in the existing researches, that is quantitative and qualitative. FREES can reflect human cognition process in the risk analysis and evaluation by adopting artificial intelligence fuzzy theory, differentiating the existing quantitative analysis model. The FREES can be applied to all the project phases from planning to operation & maintenance stage.

• Journal of the Korea institute for structural maintenance and inspection
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• v.3 no.2
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• pp.233-240
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• 1999

Even though the recent construction safety disasters not only result in the loss inside construction sites but also become to a large public disasters, safety activities are managed in an irrational way and safety rules are ignored in the construction sites which leads to occur same type of disasters repeatedly. In this paper, a fuzzy set theoretic approach to risk analysis is proposed as an alternative to the techniques currently used in the general construction projects safety. Then the concept of risk evaluation using linguistic representation of the likelihood, exposure and consequences is introduced. A risk assessment model using approximate reasoning technique base on fuzzy logic is presented to drive fuzzy values of risk and numerical example for risk analysis is also presented to illustrate the results.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.1
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• pp.16-26
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• 1997

China is one of the few countries where natural disaster strike frequently and cause heavy damage. In this paper, we mathematically develop two models to assess fuzzy risk of natural disaster in China. One is to assess the risk based on database of historical disaster effects by using information diffusion method relevant in fuzzy information analysis. In another model, we give an overview over advanced method to calculate the risk of release, exposure and consequence assessent, where information distribution technique is used to calculate basic fuzzy relationships showing historical experience of natural disasters, and fuzzy approximate inference is employed to study loss risk based on these basic relationships. We also present an examples to show how to use the first model. Result show that the model is effective for natural disaster risk assessment.

• Ocean Systems Engineering
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• v.9 no.3
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• pp.261-285
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• 2019

Nowadays in offshore industry there are emerging hazards with vague property such as act of terrorism, act of war, unforeseen natural disasters such as tsunami, etc. Therefore industry professionals such as offshore energy insurers, safety engineers and risk managers in order to determine the failure rates and frequencies for the potential hazards where there is no data available, they need to use an appropriate method to overcome this difficulty. Furthermore in conventional risk based analysis models such as when using a fault tree analysis, hazards with vague properties are normally waived and ignored. In other word in previous situations only a traditional probability based fault tree analysis could be implemented. To overcome this shortcoming fuzzy set theory is applied to fault tree analysis to combine the known and unknown data in which the pre-combined result will be determined under a fuzzy environment. This has been fulfilled by integration of a generic bow-tie based risk analysis model into the risk assessment phase of the Risk Management (RM) cycles as a backbone of the phase. For this reason Fault Tree Analysis (FTA) and Event Tree Analysis (ETA) are used to analyse one of the significant risk factors associated in offshore terminals. This process will eventually help the insurers and risk managers in marine and offshore industries to investigate the potential hazards more in detail if there is vagueness. For this purpose a case study of offshore terminal while coinciding with the nature of the Caspian Sea was decided to be examined.

• Nuclear Engineering and Technology
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• v.53 no.5
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• pp.1464-1478
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• 2021

Selective Production of Exotic Species is an innovative plant for advanced nuclear physic studies. A radioactive beam, generated by using an UCx target-ion source system, is ionized, selected and accelerated for experimental objects. Very high vacuum conditions and appropriate safety systems to storage exhaust gases are required to avoid radiological risk for operators and people. In this paper, Failure Mode, Effects, and Criticality Analysis of a preliminary design of high activity gas recovery system is performed by using a modified Fuzzy Risk Priority Number to rank the most critical components in terms of failures and human errors. Comparisons between fuzzy approach and classic application allow to show that Fuzzy Risk Priority Number is able to enhance the focus of risk assessments and to improve the safety of complex and innovative systems such as those under consideration.

• Korean Journal of Construction Engineering and Management
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• v.5 no.2 s.18
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• pp.136-143
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• 2004

This study presents a risk management methodology using fuzzy theory for early construction stage and is focused on risk identification and risk analysis. This study identifies various risk factors associated with activities clearly construction stage, then establishes the Risk Breakdown Structure(RBS) by classifying the risks into the three groups; Common risks, risks for Earth works, and risks for Foundation works. The risk analysis method presented in this study is based on the RBS that has two levels such as upper level and lower level. The risk exposure of lower level risk factors is assessed by fuzzy inference. The weight of risks is estimated by fuzzy measure. Then, the estimated risk exposures and weights are aggregated to assess the risk exposure of upper level risks by Choquet fuzzy integral. The risk exposure of upper level risks determine the priority of risk factors in view of risk management. This study performs case study to validate the proposed method. The result of case study shows that the methodology suggested in this thesis would be utilized well in evaluating risk exposure.

• Journal of the Korea Safety Management & Science
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• v.14 no.3
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• pp.119-126
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• 2012

Recently, the breakdown of online banking servers and the leakage of customer information give rise to much concern about the security of information systems in financial and banking companies in Korea. The enforcement of security for information system becomes much more important issue than earlier. However, the security reinforcement of information system is restricted by a budget. In addition, the activities' cost to secure information system from threatening are under uncertain circumstances and should be established by a human decision maker who is basically uncertain and vague. Thus, making the budget for information system is exposed to any extent of the risk for these reasons. First, we introduce brief fuzzy set theory and fuzzy AHP (Analytic Hierarchy Process) methodology. Then, the cost elements that comprise yearly budget are presented and the priorities among the cost elements are calculated by fuzzy AHP. The cost elements that are exposed to risk are evaluated from the both perspectives of the risk impact and risk occurrence possibility which are expressed as linguistic terms. To get information on the risk profiles-pessimistic, most likely, and optimistic-for each cost element, the evaluation is accomplished and the result is presented. At last, the budget ranges-minimum, mode, maximum-for each cost element are estimated with the consideration of the risk profiles.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.179-192
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• 2023

The widespread use of Cloud Computing, Internet of Things (IoT), and social media in the Information Communication Technology (ICT) field has resulted in continuous and unavoidable cyber-attacks on users and critical infrastructures worldwide. Traditional security measures such as firewalls and encryption systems are not effective in countering these sophisticated cyber-attacks. Therefore, Intrusion Detection and Prevention Systems (IDPS) are necessary to reduce the risk to an absolute minimum. Although IDPSs can detect various types of cyber-attacks with high accuracy, their performance is limited by a high false alarm rate. This study proposes a new technique called Fuzzy Logic - Objective Risk Analysis (FLORA) that can significantly reduce false positive alarm rates and maintain a high level of security against serious cyber-attacks. The FLORA model has a high fuzzy accuracy rate of 90.11% and can predict vulnerabilities with a high level of certainty. It also has a mechanism for monitoring and recording digital forensic evidence which can be used in legal prosecution proceedings in different jurisdictions.