A fuzzy expert system for aviation risk assessment

Hadjimichael, Michael

doi:10.1016/j.eswa.2008.07.081

Cited by 78 publications

(33 citation statements)

References 4 publications

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“…Fuzzy expert systems have been used in areas that require expert knowledge to make decisions while minimizing several issues, such as uncertainties and subjectivity, in the decision-making process. In general, fuzzy expert systems are applied to various domains, such as diagnosing diseases in the medical field [4,23], risk assessment in aviation [18], risk assessment in construction projects [9], and selecting superior stocks on the stock exchange [15]. For instance, Adeli and Neshat [4] proposed a fuzzy expert system to diagnose heart disease.…”

Section: Related Workmentioning

confidence: 99%

“…Often, fuzzy expert systems have been utilized to address such problems because they can provide a mechanism to simulate the judgment and reasoning of experts in a particular field. To date, many researchers have used fuzzy expert systems in different application areas to help with complex decision-making problems, such as the diagnosis of disease [4] and risk estimation in aviation [18]. These studies have shown that fuzzy expert systems can be used to systematically represent human expertise in a particular domain and to deal with imprecision and subjectivity-related issues of the decisionmaking process while making the decision-making process more effective.…”

Section: Introductionmentioning

confidence: 99%

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Risk-based test case prioritization using a fuzzy expert system

Hettiarachchi

Choi

2016

Information and Software Technology

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a b s t r a c tContext: The use of system requirements and their risks enables software testers to identify more important test cases that can reveal the faults associated with system components.Objective: The goal of this research is to make the requirements risk estimation process more systematic and precise by reducing subjectivity using a fuzzy expert system. Further, we provide empirical results that show that our proposed approach can improve the effectiveness of test case prioritization.Method: In this research, we used requirements modification status, complexity, security, and size of the software requirements as risk indicators and employed a fuzzy expert system to estimate the requirements risks. Further, we employed a semi-automated process to gather the required data for our approach and to make the risk estimation process less subjective.Results: The results of our study indicated that the prioritized tests based on our new approach can detect faults early, and also the approach can be effective at finding more faults earlier in the high-risk system components compared to the control techniques.Conclusion: We proposed an enhanced risk-based test case prioritization approach that estimates requirements risks systematically with a fuzzy expert system. With the proposed approach, testers can detect more faults earlier than with other control techniques. Further, the proposed semi-automated, systematic approach can easily be applied to industrial applications and can help improve regression testing effectiveness.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Risk-based test case prioritization using a fuzzy expert system

Hettiarachchi

Choi

2016

Information and Software Technology

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“…Risk modelling typically collects knowledge resulting from flight safety analysis, human experience and theoretical and empirical studies. The goal of aviation risk assessment is to be comprehensive, timely and proactive, and this is why the analysis methods should be enhanced [23].…”

Section: Safety Tools and Systemsmentioning

confidence: 99%

“…In aviation, the quantitative assessment of risk is particularly challenging, because the deviation events are extremely rare and the causal factors are non-linearly related to the events which makes them difficult to quantify [23]. The eventuality for the incident or accident occurring may be markedly reduced in case the risks can be efficiently diagnosed [24].…”

Section: Safety Tools and Systemsmentioning

confidence: 99%

Data Mining Challenges in the Management of Aviation Safety

Sjöblom

2014

IFIP Advances in Information and Communication Technology

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Part 2: Digital SocietyInternational audienceThis paper introduces aviation safety data analysis as an important application area for data mining. Safety is a key strategic management concern for safety-critical industries and management needs new, more efficient tools and methods for more effective management routines. The aviation field is confronted with increasing challenges to provide safe and fluent services. Air travel has grown steadily during the last decades with a direct impact on the air traffic control. At the same time, the competition has become tougher because of increasing fuel prices and growing demand for air travel

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“…One of the most interesting papers [29] describes the expert system that was created to assist the take-off and landing risk assessment. The problem of flight crews' duty hours planning was undertaken by Teodorović and Lučić [30].…”

Section: Introductionmentioning

confidence: 99%

The Influence of Errors in Visualization Systems on the Level of Safety Threat in Air Traffic

Ferduła

Skorupski

2018

Journal of Advanced Transportation

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Air traffic management is carried out by air traffic controllers assisted by complex technical systems that provide them with visualization of the traffic situation. In practice, visualization systems errors sometimes occur. The purpose of this paper is to determine the impact of errors of different types on the safety of the air traffic. The assessment of the threat level is influenced by subjective factors and cannot be expressed precisely. Therefore, the fuzzy reasoning theory has been used. The developed fuzzy model has been used to obtain a tool for simulation of the impact of various factors on traffic safety assessment. The results obtained indicate that the most important determinants of safety are the time when the air traffic controller remains unaware of the breakdown and the total time he/she does not have full knowledge of the traffic situation. It has been found that the key role for the proper operation of the air traffic visualization system and the restoration of full situational awareness is played by self-diagnostic systems that can restore the system's correct functioning without even the controller being aware of the error occurrence. Their role in ensuring safety might be even greater than redundancy which is commonly used.

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A fuzzy expert system for aviation risk assessment

Cited by 78 publications

References 4 publications

Risk-based test case prioritization using a fuzzy expert system

Risk-based test case prioritization using a fuzzy expert system

Data Mining Challenges in the Management of Aviation Safety

The Influence of Errors in Visualization Systems on the Level of Safety Threat in Air Traffic

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