Application of Fuzzy Logic Inference System, Interval Numbers and Mapping Operator for Determination of Risk Level
Background & objective: Due to the features such as intuitive graphical appearance, ease of perception and straightforward applicability, risk matrix has become as one of the most used risk assessment tools. On the other hand, features such as the lack of precision in the classification of risk...
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| Format: | Article |
| Language: | fas |
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Hamadan University of Medical Sciences
2015-12-01
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| Series: | Muhandisī-i bihdāsht-i ḥirfah/ī |
| Subjects: | |
| Online Access: | http://johe.umsha.ac.ir/browse.php?a_id=137&slc_lang=en&sid=1&ftxt=1 |
| _version_ | 1811258391308271616 |
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| author | Mohsen Omidvar Fereshteh Nirumand |
| author_facet | Mohsen Omidvar Fereshteh Nirumand |
| author_sort | Mohsen Omidvar |
| collection | DOAJ |
| description | Background & objective: Due to the features such as intuitive graphical appearance, ease of perception and straightforward applicability, risk matrix has become as one of the most used risk assessment tools. On the other hand, features such as the lack of precision in the classification of risk index, as well as subjective computational process, has limited its use. In order to solve this problem, in the current study we used fuzzy logic inference systems and mathematical operators (interval numbers and mapping operator).
Methods: In this study, first 10 risk scenarios in the excavation and piping process were selected, then the outcome of the risk assessment were studied using four types of matrix including traditional (ORM), displaced cells (RCM) , extended (ERM) and fuzzy (FRM) risk matrixes.
Results: The results showed that the use of FRM and ERM matrix have prority, due to the high level of " Risk Tie Density" (RTD) and "Risk Level Density" (RLD) in the ORM and RCM matrix, as well as more accurate results presented in FRM and ERM, in risk assessment. While, FRM matrix provides more reliable results due to the application of fuzzy membership functions.
Conclusion: Using new mathematical issues such as fuzzy sets and arithmetic and mapping operators for risk assessment could improve the accuracy of risk matrix and increase the reliability of the risk assessment results, when the accurate data are not available, or its data are avaliable in a limit range. |
| first_indexed | 2024-04-12T18:13:39Z |
| format | Article |
| id | doaj.art-0a4034e797614e3594fbf79fb67b3900 |
| institution | Directory Open Access Journal |
| issn | 2383-3378 2383-3378 |
| language | fas |
| last_indexed | 2024-04-12T18:13:39Z |
| publishDate | 2015-12-01 |
| publisher | Hamadan University of Medical Sciences |
| record_format | Article |
| series | Muhandisī-i bihdāsht-i ḥirfah/ī |
| spelling | doaj.art-0a4034e797614e3594fbf79fb67b39002022-12-22T03:21:43ZfasHamadan University of Medical SciencesMuhandisī-i bihdāsht-i ḥirfah/ī2383-33782383-33782015-12-01235565Application of Fuzzy Logic Inference System, Interval Numbers and Mapping Operator for Determination of Risk LevelMohsen Omidvar Fereshteh NirumandBackground & objective: Due to the features such as intuitive graphical appearance, ease of perception and straightforward applicability, risk matrix has become as one of the most used risk assessment tools. On the other hand, features such as the lack of precision in the classification of risk index, as well as subjective computational process, has limited its use. In order to solve this problem, in the current study we used fuzzy logic inference systems and mathematical operators (interval numbers and mapping operator). Methods: In this study, first 10 risk scenarios in the excavation and piping process were selected, then the outcome of the risk assessment were studied using four types of matrix including traditional (ORM), displaced cells (RCM) , extended (ERM) and fuzzy (FRM) risk matrixes. Results: The results showed that the use of FRM and ERM matrix have prority, due to the high level of " Risk Tie Density" (RTD) and "Risk Level Density" (RLD) in the ORM and RCM matrix, as well as more accurate results presented in FRM and ERM, in risk assessment. While, FRM matrix provides more reliable results due to the application of fuzzy membership functions. Conclusion: Using new mathematical issues such as fuzzy sets and arithmetic and mapping operators for risk assessment could improve the accuracy of risk matrix and increase the reliability of the risk assessment results, when the accurate data are not available, or its data are avaliable in a limit range.http://johe.umsha.ac.ir/browse.php?a_id=137&slc_lang=en&sid=1&ftxt=1Risk MatrixUncertaintyFuzzy Logic SystemArithmetic OperatorsMapping Operator |
| spellingShingle | Mohsen Omidvar Fereshteh Nirumand Application of Fuzzy Logic Inference System, Interval Numbers and Mapping Operator for Determination of Risk Level Muhandisī-i bihdāsht-i ḥirfah/ī Risk Matrix Uncertainty Fuzzy Logic System Arithmetic Operators Mapping Operator |
| title | Application of Fuzzy Logic Inference System, Interval Numbers and Mapping Operator for Determination of Risk Level |
| title_full | Application of Fuzzy Logic Inference System, Interval Numbers and Mapping Operator for Determination of Risk Level |
| title_fullStr | Application of Fuzzy Logic Inference System, Interval Numbers and Mapping Operator for Determination of Risk Level |
| title_full_unstemmed | Application of Fuzzy Logic Inference System, Interval Numbers and Mapping Operator for Determination of Risk Level |
| title_short | Application of Fuzzy Logic Inference System, Interval Numbers and Mapping Operator for Determination of Risk Level |
| title_sort | application of fuzzy logic inference system interval numbers and mapping operator for determination of risk level |
| topic | Risk Matrix Uncertainty Fuzzy Logic System Arithmetic Operators Mapping Operator |
| url | http://johe.umsha.ac.ir/browse.php?a_id=137&slc_lang=en&sid=1&ftxt=1 |
| work_keys_str_mv | AT mohsenomidvar applicationoffuzzylogicinferencesystemintervalnumbersandmappingoperatorfordeterminationofrisklevel AT fereshtehnirumand applicationoffuzzylogicinferencesystemintervalnumbersandmappingoperatorfordeterminationofrisklevel |