142 research outputs found

    Fuzzy expert systems in civil engineering

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    Probability Transform Based on the Ordered Weighted Averaging and Entropy Difference

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    Dempster-Shafer evidence theory can handle imprecise and unknown information, which has attracted many people. In most cases, the mass function can be translated into the probability, which is useful to expand the applications of the D-S evidence theory. However, how to reasonably transfer the mass function to the probability distribution is still an open issue. Hence, the paper proposed a new probability transform method based on the ordered weighted averaging and entropy difference. The new method calculates weights by ordered weighted averaging, and adds entropy difference as one of the measurement indicators. Then achieved the transformation of the minimum entropy difference by adjusting the parameter r of the weight function. Finally, some numerical examples are given to prove that new method is more reasonable and effective

    Wasserstein distance-based probabilistic linguistic TODIM method with application to the evaluation of sustainable rural tourism potential

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    The evaluation of sustainable rural tourism potential is a key work in sustainable rural tourism development. Due to the complexity of the rural tourism development situation and the limited cognition of people, most of the assessment problems for sustainable rural tourism potential are highly uncertain, which brings challenges to the characterisation and measurement of evaluation information. Besides, decision-makers (DMs) usually do not exhibit complete rationality in the practical evaluation process. To tackle such problems, this paper proposes a new behaviour multi-attribute group decision-making (MAGDM) method with probabilistic linguistic terms sets (PLTSs) by integrating Wasserstein distance measure into TODIM (an acronym in Portuguese of interactive and multicriteria decision making) method. Firstly, a new Wasserstein-based distance measure with PLTSs is defined, and some properties of the proposed distance are developed. Secondly, based on the correlation coefficient among attributes and standard deviation of each attribute, an attribute weight determination method (called PL-CRITIC method) is proposed. Subsequently, a Wasserstein distance-based probabilistic linguistic TODIM method is developed. Finally, the proposed method is applied to the evaluation of sustainable rural tourism potential, along with sensitivity and comparative analyses, as a means of illustrating the effectiveness and advantages of the new method

    A RISK-BASED VERIFICATION FRAMEWORK FOR OFFSHORE WIND FARM DEVELOPMENT: DESIGN, INSTALLATION, OPERATIONS AND MAINTENANCE OF OFFSHORE WIND TURBINES

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    This thesis encompasses a holistic review of the development trends in wind turbine technology (onshore and offshore) and the challenges perceived at the stages of design, construction and operations of modern-day wind energy technology (Friedrich and Lukas, 2017). The main focus of this study is to evaluate the risks associated with offshore wind farm development (OWFD). This is achieved by first estimating those perceived risks, understanding the relative importance of each individual risk, and carrying out an assessment using a specialist analytical tool known as AHiP-Evi. AHiP-Evi was developed through a combination of application of Analytic Hierarchy Process (AHP) and Evidential Reasoning (ER) techniques. The AHP was used to ascertain the weighting of the respective risk variables according to their relative importance, while the ER was used to evaluate the aggregated influence of the collective risk variables associated with the OWFD. Finally, a specific modelling tool known as BN-SAT (Bayesian Network Sensitivity Analysis Technique) was developed to evaluate the probabilities of occurrence of the variable nodes and their overall impacts on the decision node (OWFD). The BN-SAT is comprised of a combination of Bayesian networks (BNs) concepts and a sensitivity analysis (SA) approach. The AHiP-Evi model initially developed in this study is transformed into the BN structure in order to compute the conditional and unconditional prior probability for each starting node using the NETICA analytical software to determine the aggregated impact of the specific risk variables on the OWFD. The outcome from this modelling analysis is then compared to the initial assessment carried out by the application of the AHiP-Evi modelling tool in order to validate the robustness of both modelling tools. In the case study of this research, the percentage difference of the outcomes of the two models is insignificant, which demonstrates the fact that both systems are effective. The Fuzzy Analytic Hierarchy Process (FAHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) were integrated to develop a specific model for the selection of best-case risk management technique (RMT). Based on the decision makers’ (DMs) aggregated judgements, it was possible to compute the values and determine the best-case RMT dependent on the decision variables driving the decision - for example, costs and benefits, through the developed integrated model known as FAHP-FTOPSIS. The outcome of this selection model has been seen to be reasonably practical and a successful conclusion of the research contribution. Awareness of the aggregated impact of the risk variables is important in making the decision about appropriate investments in a strategic improvement of risk management and efficient resource allocations to the offshore wind industry

    Formal fire safety assessment of passenger ships

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    Fire has been a major cause of ship's accidents throughout maritime history. It is by far the most serious threat to life and the environment as passenger ships get larger and more sophisticated. It is also impossible to protect a passenger vessel against all hazards. Despite the fact that a passenger ship contains potential fire hazards in the engine room space, accommodation zone and electrical systems, etc, the single most important fire hazard onboard a ship may be the man himself, either unintentionally or intentionally. 'Fire safety on passenger vessel' has continued to be the focus of attention on passenger ships. The work described in this thesis is concerned with the application of Formal Fire Safety Assessment to passenger ships. The traditional way of conducting a Formal Safety Assessment (FSA) employs typical fire safety analysis methods that require a certain amount of data. Most fire accident data available for passenger vessels is associated with a high degree of uncertainty and considered to be unreliable. As such, the research carried out in this thesis is directed at the development of novel fire safety analysis methods to address this problem. This thesis proposed several subjective fire safety analysis methods for passenger vessels within the FSA methodology. Also, it concentrates on developing an advanced approach for passenger ships. A few novel safety analysis and synthesis methodologies are presented to integrate fire safety assessment with decision-making techniques so that fire safety can be taken into account from the concept design /operation stages of passenger ships. This is to ensure a more controlled development process permitting decisions regarding design and operation to be made based on fire safety assessment. Finally, this thesis is concluded by summarising the results of this research project and the areas where further effort is required to improve the developed methodologies

    Development of an Efficient Planned Maintenance Framework for Marine and Offshore Machinery Operating under Highly Uncertain Environment

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    The constantly increasing complexity of marine and offshore machinery is a consequence of a constant improvement in ship powering, automation, specialisation in cargo transport, new ship types, as well as an effort to make the sea transport more economic. Therefore, the criteria of reliability, availability and maintainability have become very important factors in the process of marine machinery design, operation and maintenance. An important finding from the literature exposed that failure to marine machinery can cause both direct and indirect economic damage with a long-term financial consequence. Notably, many cases of machinery failures reported in databases were as a result of near misses and incidents which are potential accident indicators. Moreover, experience has shown that modelling of past accident events and scenarios can provide insights into how a machinery failure can be subsisted even if it is not avoidable, also a basis for risk analysis of the machinery in order to reveal its vulnerabilities. This research investigates the following modelling approach in order to improve the efficiency of marine and offshore machinery operating under highly uncertain environment. Firstly, this study makes full use of evidential reasoning’s advantage to propose a novel fuzzy evidential reasoning sensitivity analysis method (FER-SAM) to facilitate the assessment of operational uncertainties (trend analysis, family analysis, environmental analysis, design analysis, and human reliability analysis) in ship cranes. Secondly, a fuzzy rule based sensitivity analysis methodology is proposed as a maintenance prediction model for oil-wetted gearbox and bearing with emphasis on ship cranes by formulating a fuzzy logic box (diagnostic table), which provides the ship crane operators with a means to predict possible impending failure without having to dismantle the crane. Thirdly, experience has shown that it is not financially possible to employ all the suggested maintenance strategies in the literature. Thus, this study proposed a fuzzy TOPSIS approach that can help the maintenance engineers to select appropriate strategies aimed at enhancing the performance of the marine and offshore machinery. Finally, the developed models are integrated in order to facilitate a generic planned maintenance framework for robust improvement and management, especially in situations where conventional planned maintenance techniques cannot be implemented with confidence due to data deficiency

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    Decision Maps for Distributed Scenario-Based Multi-Criteria Decision Support

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    This thesis presents the Decision Map approach to support decision-makers facing complex uncertain problems that defy standardised solutions. First, scenarios are generated in a distributed manner: the reasoning processes can be adapted to the problem at hand whilst respecting constraints in time and availability of experts. Second, by integrating scenarios and MCDA, this approach facilitates robust decision-making respecting multiple criteria in a transparent well-structured manner

    A Comprehensive Star Rating Approach for Cruise Ships Based on Interactive Group Decision Making with Personalized Individual Semantics

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    This article proposes a comprehensive star rating approach for cruise ships by the combination of subject and objective evaluation. To do that, it firstly established a index system of star rating for cruise ships. Then, the modified TOPSIS is adopted to tackle objective data for obtaining star ratings for basic cruise indicators and service capabilities of cruise ships. Thus, the concept of distributed linguistic star rating function (DLSRF) is defined to analyze the subjective evaluation from experts and users. Hence, a novel weight calculation method with interactive group decision making is presented to assign the importance of the main indicators. Particularly, in order to enable decision makers to effectively deal with the uncertainty in this star rating process, it adopts the personalized individual semantics (PIS) model. Finally, data of nine cruise ships is collected to obtain their final star rating results and some suggestions for improving cruise service capabilities and star indicators were put forward.National Natural Science Foundation of China (NSFC) 71971135,72001134,72071056 China Scholarship Council 202108310183 Innovative Talent Training Project of Graduate Students in Shanghai Maritime University of China 2021YBR00
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