Fuzzy Expert Research Articles

Consensus-based failure mode and effect analysis in group decision-making with incomplete weights of risk factors: Case study of stereotactic body radiation therapy for lung cancer

Failure mode and effect analysis (FMEA) is a widely used management technique to identify potential failure modes in products, processes, systems, and services to assign limited resources for implementing improvement efforts. For the FMEA with a number of experts, the experts may take different influences on the decision-making process due to the difference between individual rationality and cognition and the influence of social relations. Besides, incomplete weights of risk factors are vital to capturing the fuzziness of experts’ evaluation. Therefore, this paper proposes a consensus-based FMEA method to explore that how cooperative relationship network of experts, the consensus process, and incomplete weight information of risk factors in FMEA influence the decision-making process. First, a consensus reaching process considering cooperative relationships between experts, the self-confidence of experts, and minimum adjustment of expert opinion is proposed to derive a collective evaluation of group. Afterward, the stochastic multicriteria acceptability analysis method is integrated with the gained and lost dominance score method to deal with incomplete weights of risk factors in the FMEA. The proposed method is employed in a case study about ranking the failure modes of stereotactic body radiation therapy for lung cancer patients. The robustness and feasibility of the proposed method are validated by comparative analysis.

Price estimation based on business model pricing strategy and fuzzy logic

Pricing, as one of the most important aspects of a business, should be taken seriously. Whatever affects a company's pricing system tends to affect its profits and losses as wall. Currently, many manufacturing companies fix product prices manually by member of an organization's management team. However, due to the imperfect nature of humans, an extremely low or high price may be fixed, which is detrimental to the company in either case. This paper proposes the developement of a fuzzy-based price expert system (Expert Fuzzy Price (EFP)) for manufacturing companies. This system will be able to recommend appropriate prices for products in manufacturing companies based on four major pricing strategic goals, namely : Product Demand, Price Skimming, Competition Price, and Target population.

A Hybrid Intuitionistic Fuzzy Group Decision Framework and Its Application in Urban Rail Transit System Selection

The selection of an urban rail transit system from the perspective of green and low carbon can not only promote the construction of an urban rail transit system but also have a positive impact on urban green development. Considering the uncertainty caused by different conflict criteria and the fuzziness of decision-making experts’ cognition in the selection process of a rail transit system, this paper proposes a hybrid intuitionistic fuzzy MCGDM framework to determine the priority of a rail transit system. To begin with, the weights of experts are determined based on the improved similarity method. Secondly, the subjective weight and objective weight of the criterion are calculated, respectively, according to the DEMATEL and CRITIC methods, and the comprehensive weight is calculated by the linear integration method. Thirdly, considering the regret degree and risk preference of experts, the COPRAS method based on regret theory is propounded to determine the prioritization of urban rail transit system ranking. Finally, urban rail transit system selection of City N is selected for the case study to illustrate the feasibility and effectiveness of the developed method. The results show that a metro system (P1) is the most suitable urban rail transit system for the construction of city N, followed by a municipal railway system (P7). Sensitivity analysis is conducted to illustrate the stability and robustness of the designed decision framework. Comparative analysis is also utilized to validate the efficacy, feasibility and practicability of the propounded methodology.

Professional Well-Being and Work Engagement of University Teachers Based on Expert Fuzzy Data and SOR Theory

The study of the professional well-being of university teachers not only encompasses the quality of teachers’ personal lives but can also reflect satisfaction and loyalty to their careers and has an irreplaceable impact on students’ thinking and political education. The article starts from explaining the connotation of professional happiness of university teachers and analyses the significance of improving the professional happiness of university teachers. Through a questionnaire survey of 504 young teachers in Jiangxi province universities, based on expert fuzzy data and SOR theory, the article analyses various influencing factors in this framework and finds that the current professional happiness of young teachers in universities is positively related to various influencing factors. Based on expert fuzzy data and SOR theory, this paper investigates the professional happiness and work commitment of college teachers. The results of several research tests show that young college teachers have different professional happiness under different conditions, which indicates that material incentives can improve the professional happiness of young college teachers to a certain extent. Therefore, the professional happiness of young university teachers can be improved in terms of enhancing comprehensive quality, improving social status, strengthening humanistic care, broadening growth platform, and establishing scientific system.

An extended MABAC method based on prospect theory with unknown weight information under Fermatean fuzzy environment for risk investment assessment in B&R.

The assessment of investment risk for the countries along the route in Belt and Road (B&R) can be deemed as a multiple criteria group decision making (MCGDM) issue since multiple investment options based on diverse criterions are assessment by experts. Pondering that the complexity and uncertainty of the assessment setting and the cognition fuzziness and psychological behavior of experts bring challenges to risk assessment, this paper designed an integrated MCGDM risk investment evaluation framework by synthesizing MABAC method and prospect theory under Fermatean fuzzy setting. Firstly, a Fermatean fuzzy interactive distance measure is presented to ascertain the weight of evaluation experts and criterions. Next, some Fermatean fuzzy Frank aggregation operators based upon the proposed Frank operations are developed to fuse Fermatean fuzzy information efficiently. In addition, an innovative evaluation framework for risk investment is designed based on improved prospect theory MABAC and CRITIC approaches. Conclusively, an empirical concerning risk investment issues in B&R is employed to confirm the applicability and feasibility of the constructed evaluation framework, involving the simulation experiments on sensitivity analysis and contrast studies. The assessment information provided by investors using the linguistic assessment terms based upon their cognition ability of them. These outcomes obtained by the propounded method and comparison analysis further emphasize the validity and salient merits of the propounded framework and provide several auxiliary suggestions for investors.

Product evaluation through multi-criteria decision making based on fuzzy parameterized Pythagorean fuzzy hypersoft expert set

<abstract><p>In many real-world decision-making situations, uncertain nature of parameters is to be discussed to have unbiased and reliable decisions. Most of the existing literature on fuzzy soft set and its related structures ignored the uncertain parametric attitudes. The concept of fuzzy parameterization is launched to tackle the limitations of existing soft set-like models. Several extensions have already been introduced by using the concept of fuzzy parameterization. In this research, a novel extension, fuzzy parameterized Pythagorean fuzzy hypersoft expert set is aimed to be characterized. This model is more flexible and reliable as compared to existing models because it addresses their insufficiencies for the consideration of multi-argument approximate function. With the entitlement of this function, it tackles the real-life scenarios where each attribute is meant to be further classified into its respective sub-attribute valued disjoint set. The characterization of fuzzy parameterized Pythagorean fuzzy hypersoft expert set is accomplished by employing theoretic, axiomatic and algorithmic approaches. In order to validate the proposed model, an algorithm is proposed to study its role in decision-making while dealing with real-world problem. Moreover, the proposed model is compared with the most relevant existing models to assess its advantageous aspects.</p></abstract>

Fuzzy logic expert system-based machinability analysis in end milling of aluminium nitride ceramic

Fuzzy logic expert system-based machinability analysis in end milling of aluminium nitride ceramic

Human Factor Risk Modeling for Shipyard Operation by Mapping Fuzzy Fault Tree into Bayesian Network.

The operational activities conducted in a shipyard are exposed to high risk associated with human factors. To investigate human factors involved in shipyard operational accidents, a double-nested model was proposed in the present study. The modified human factor analysis classification system (HFACS) was applied to identify the human factors involved in the accidents, the results of which were then converted into diverse components of a fault tree and, as a result, a single-level nested model was established. For the development of a double-nested model, the structured fault tree was mapped into a Bayesian network (BN), which can be simulated with the obtained prior probabilities of parent nodes and the conditional probability table by fuzzy theory and expert elicitation. Finally, the developed BN model is simulated for various scenarios to analyze the identified human factors by means of structural analysis, path dependencies and sensitivity analysis. The general interpretation of these analysis verify the effectiveness of the proposed methodology to evaluate the human factor risks involved in operational accidents in a shipyard.

A Study of Bipolar Fuzzy Soft Sets and Its Application in Decision-Making Problems

We live in a society where we have to deal with so many social issues daily, and making a right choice is everyone’s main concern. This study is based on the selection of right university while getting admission which is the core issue for students nowadays. We are concerned with bipolar fuzzy multicriteria decision-making methods. The main purpose is to provide guidance to the students for determining the best university and evaluating the factors that are affecting while getting admission. We thus combined bipolar fuzzy and soft expert sets to give multicriteria decision-making approach that overcomes the issues that arise while taking decisions. This study involves the development of structural hierarchical models of parameters and the implementation of soft expert sets to make the decision-making problem much more precise by introducing a new algorithm. Thus, this model is helpful for multicriteria decision making and can be used for university selection and thus suitable for education sector as well.

Sustainable development evaluation on wind power compressed air energy storage projects based on multi-source heterogeneous data

According to the requirement of energy sustainable development strategy in Jilin province, this paper evaluates the performance of wind power coupling compressed air energy storage projects for a wind farm in Jilin from the perspective of sustainability. Firstly, a sustainable criteria system is established from economic, social and ecological dimensions, and 10 secondary criteria are given. Secondly, to fully express the hesitancy and fuzziness of experts, linguistic fuzzy hesitant sets (LFHSs) are used to describe the subjective evaluation information. And then, the cloud model is developed to deal with the randomness and fuzziness of LFHS. Thirdly, a multi criteria decision-making model based on improved Choquet fuzzy integral and deviation degree is proposed for a multi criteria evaluation problem with initial data in the form of crisp values, interval numbers and linguistic fuzzy hesitant sets. The deviation degree can deal with multi-source heterogeneous data and Choquet fuzzy integral improved with Mobius transformation can eliminate the overlap information between criteria. Finally, the case study in Jilin is given to illustrate the effective of the proposed evaluation criteria and technique. From the results, the project 4: wind power coupling compressed air energy storage system with meshing switch is the most suitable alternative for the wand farm, followed by the project of wind power coupling compressed air energy storage system with variable configuration. Moreover, the sensitivity analysis reveals that the project 4 always occupies its top ranking when its weight is floating within a certain range. At last, some policy implications to promote wind power industry are given for the government.

Fazi logički ekspertski sistem za procenu stanja izolacionog sistema statora VN motora

During operation, the electrical insulation system (EIS) of high-voltage motors is exposed to various factors that can accelerate its aging. Timely knowledge of the actual state of the EIS is of great help in allocating funds for service activities. The condition of the EIS of the HV motor can be assessed to some extent by performing available electrical tests. A major shortcoming is the lack of accuracy and the lack of well-defined criteria in the current standards. In that way, a potential error can bias the evaluation of recorded results. The paper proposes the use of a fuzzy logic expert system for assessing the condition of EIS stators of HV motors based on the results of electrical measurements. Also, the proposed fuzzy approach is fully discussed. The created expert system fully relies on the criteria defined in the IS32-Internal Standard of PE EPS.

A Comparative Study of FCSM, FSAW and TOPSIS Techniques using Triangular Fuzzy Numbers

This paper presents a comparative study of different techniques used for fuzzy multi-criteria expert’s decision-making (FMCEDM). These include CSM1, CSM2, CSM3, FSAW, and TOPSIS. We developed the methods CSM1 and CSM3 respectively and studied their validity by comparing their illustration results with that of CSM2, FSAW and TOPSIS. Expert’s ratings and weights were assigned in linguistic variables in terms of triangular fuzzy numbers (TFNs) to the FMCEDM problem. Airport performance evaluation and a personnel selection problem were studied as alternatives under different decision criteria and experts.

Enhanced humanoid assisted human interaction model based on linear structural modeling for knowledge representation

Certain rules and regulations are adapted to the linguistic production model to support the decision of human computer interaction using linguistic protection rule method. This paper proposes linear linguistic advanced structural modeling (LLASM) approach to develop weighted linguistic reasoning (WLR) algorithm for the purpose of reasoning and knowledge representation. In this article human computer interaction faces optimal flow and job Characteristics experience using individual computers in the workplace which helps to overcome the issues using LLASM in a variety of organizations with Robotic assistance for verbal and non-verbal sequence using humanoid robot. This model introduces global weight and local knowledge fuzzy rules to determine the optimal flow and job characterization problem faced in linguistic reasoning method. Here, The Weighted linguistic reasoning algorithm allows fuzzy rule-based expert systems with the help of the LLASM method to execute the intelligent and flexible knowledge reasoning model with robotic assistance. Finally, case studies are presented to show the effectiveness of the re-scheduling process which benefits the proposed method using the Linguistic reasoning model.

Impacts of computer game concept formulation on project development processes: a FIOWA explorative case study

The development of computer game projects is different from that of traditional software development projects, which often require clear system specifications for to achieve effective team coordination and cooperation. This unique context requires particular attention for effective project management and project success. Nevertheless, computer game development projects involve different expert groups working on different parts of the computer game design who need to have a shared understanding of the game vision/concept. Arriving at a shared understanding of the application domain among these diversified groups within the project team can be difficult and challenging. Coordination and communication within this diverse talent team is critical to conveying the intent and details of a game’s design. In this study, we will explore how coordination practices across different fuzzy OWA expert groups can be enhanced by shared concept formulation during the computer game development process. Based upon an exploratory case study, the result indicates that the shared game vision serves as an important part of the team task mental model, which, in turn, provides the cognitive foundation for the coordination and cooperation needed among team members.

Modeling the Crowdsourcing Effective Factors on Marketing in Tourism Industry

Current era is customer-orientation era and organizations try hard to satisfy their customers and do their best in marketing. There are numerous factors affect customer satisfaction. One of these important factors is crowdsourcing. Crowdsourcing is one of the emerging Web based phenomenon which has attracted great attention from both customers and researchers over the years. Therefore, to investigate it and its effective factors is needed. So, this research is modeling the crowdsourcing effective factors on marketing in tourism industry. Current research is applied one and seeks to identify crowdsourcing effective factors on customer satisfaction in tourism industry. Also, research method is descriptive-survey. So, the independent and dependent variables have been introduced at the first part by literature review. Then, the identified factors in the model has been validated by using judgmental method and 7 experts’ viewpoints in tourism field. To present the final conceptual model, fuzzy cognitive mapping and expert mind map drawing have been used. Findings have indicated that among the technology factor indexes, the “social networks” index had the most effect; among environmental factor indexes, the “applying competitive competitiveness” index had the most effect; among the product market price factor indexes, the “consumer price elasticity” index had the most effect; among the executive decisions factor indexes, the “high income for better planning” index had the most effect; among the financial flows factor indexes, the “organizing suitable individual” index had the most effect; among the motive forces factor indexes, the “task attractiveness” index had the most effect; among the main factors indexes, the “using the newest sources” index had the most effect and among task features indexes, the “creativity in performing the task” index had the most effect. Also, recommendations have been presented.

An assessment model of monitoring risk in deep excavation based on fuzzy theory

In order to better evaluate the monitoring risk of deep excavation, an assessment model based on fuzzy theory was established by combining the uncertainty and membership degree of evaluation indexes with the fuzziness of experts’ comments. Firstly, considering the risk sources as evaluation indexes, the monitoring risk evaluation system for deep excavation was establish, and the risk evaluation function was constructed. Secondly, the risk assessment model based on fuzzy theory was put forward, analytic hierarchy process was used to determine the weight of evaluation indexes, and expert evaluation weight was introduced to correct the evaluation function. Finally, comprehensive risk grade in deep excavation was obtained and the risk decisions were put forward by calculating the value of modified evaluation function. Through the application of the monitoring risk assessment model in the deep excavation of World Trade Group, the results are in accordance with the engineering practice. The results suggest that the model based on fuzzy theory is efficient for evaluating the monitoring risks and can be used in the application of deep excavation evaluation. Meanwhile, the applicability and accuracy of the assessment model are verified.

Risk assessment of urban rooftop distributed PV in energy performance contracting (EPC) projects: An extended HFLTS-DEMATEL fuzzy synthetic evaluation analysis

Promoted by the policy, urban rooftop distributed photovoltaic (URDPV) has developed rapidly in China. Besides, the government is gradually applying energy performance contracting (EPC) mode to this field making use of urban rooftop resources and energy service companies’ (ECOs’) technological advantages, but there are still obstacles to further development. One of the main reasons that restrict the further development of EPC-URDPV projects in China is the lack of effective risk assessment method. This paper aims to identify the critical risk factors (CRFs) for such projects, and propose a comprehensive risk assessment framework. Firstly, 11 CRFs are identified based on the literature review and 4-dimensional risk analysis to composed the risk assessment index system. Secondly, the weights of CRFs are determined by the intuitionistic fuzzy-decision making trial and evaluation laboratory (IF-DEMATEL) method. It is worth noting that this paper uses the hesitant fuzzy linguistic term sets (HFLTS) to obtain evaluation information to ensure the completeness and fuzziness of experts’ viewpoints. Then, an extended HFLTS-DEMATEL fuzzy synthetic evaluation method is used to conduct risk assessment. The evaluation results show that the risk levels of EPC-URDPV projects in most study areas are at “Medium” and “Relatively Low” state. The risk level of projects in Shanghai and Fujian is “Relatively High”. Sensitivity analysis results show the stability and reliability of the model. After considering the causes of risk and relevant stakeholders, a risk response is proposed. This study can enrich the methods in the field of risk assessment and provide insightful references to PV investors, decision makers.

Intelligent Cost-Oriented Manufacturing Applications to Energy Buildings using Fuzzy Experts

The manufacturing industry faces currently and in the near future due to the information society, very important challenges. New data, network, automation, digital customer interfaces and many new advancements have brought us Industry 4.0. Cost-oriented manufacturing methods and tools play a major role in the smooth and effective operation of an industry. Industry 4.0 or Smart Manufacturing as has been called by some, describes the new era of the “intelligent environment”, in which formerly separate subsystems, components and processes link together through many industrial networking protocols to produce intelligent data and transforms our daily lives. Intelligent cost-oriented concepts and practices are very important for energy savings of a building. The human needs must be taken into consideration when automation is used for Building Energy Management Systems (BEMS).

Identification and prioritisation of the critical success factors for research project-based organisations using fuzzy analytic hierarchy process

The main purpose of this study is to identify and prioritise critical success factors (CSFs) of research project-based organisations in the context of Iran using fuzzy analytic hierarchy process (FAHP) technique. In order to do so, at the first step based on an in-depth review of the relevant literature a questionnaire and holding interviews with the experts of this domain a questionnaire was designed and distributed among professionals and its validity and reliability was investigated and confirmed, leading to the structural tree of the model. Then, the second questionnaire in the form paired-wise comparison was designed, and the weights and ranking of the main CSFs and their related sub-factors were calculated using fuzzy AHP technique and expert choice software. Results reveal that the 'project factors' with a weight of 0.445 is the most important factor among the other identified factors, namely, 'personality factors', 'organisational factors' and 'environmental factors'.

Prediction of Weld Penetration Size Factor (WPSF) of TIG Mild Steel Weldment Using Fuzzy Logic

Predicting weld responses is a very important but difficult area in the field of welding which can greatly reduce the overall cost of try and error method for any fabrication industry. Fuzzy logic expert tool was used to predict the weld penetration size factor of a weld. The aim of this study is to predict the weld penetration size factor (WPSF) of TIG mild steel welds using fuzzy logic. In this study, the weld specimens were produced using the TIG welding process guided by the central composite experimental design, and thereafter the weld penetration size factor (WPSF) was measured. The process parameters include the voltage, current, gas flow rate and welding speed. The model’s significance, strength and adequacy were checked; for fuzzy logic, fuzzification was done using fuzzy linguistic variable, fuzzy linguistic terms and membership function after which an inference was made based on a set of rules and the output result was defuzzified to a crisp output. Fuzzy logic predicted beyond the boundaries of the given range of parameters. The model developed has proven to be very effective in predicting responses even before actual weld is initiated.