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This paper indicates that most of fuzzy translating rules for a fuzzy conditional proposition “If x is A then y is B” with A and B being fuzzy concepts can lead to very reasonable consequences which fit our intuition with respect to several criteria such as modus ponens and modus tollens. Moreover, it is shown that a syllogism holds for most of the methods under the new compositions, though they do not always satisfy the syllogism under the max‐min composition.

Expert systems are computer-based systems that mimic the logical processes of human experts or organizations to give advice in a specific domain of knowledge. Fuzzy expert systems use fuzzy logic to handle uncertainties generated by imprecise, incomplete and/or vague information. The purpose of this paper is to present a comprehensive review of the methods and applications in fuzzy expert systems.

The authors have carefully reviewed 281 journal publications and 149 conference proceedings published over the past 37 years since 1982. The authors grouped the journal publications and conference proceedings separately accordingly to the methods, application domains, tools and inference systems.

The authors have synthesized the findings and proposed useful suggestions for future research directions. The authors show that the most common use of fuzzy expert systems is in the medical field.

Fuzzy logic can be used to manage uncertainty in expert systems and solve problems that cannot be solved effectively with conventional methods. In this study, the authors present a comprehensive review of the methods and applications in fuzzy expert systems which could be useful for practicing managers developing expert systems under uncertainty.

A problem of handling fuzzy quantities in a process of knowledge acquisition and deriving an inference mechanism by means of fuzzy relation equations is studied in extensive way. It is clearly pointed out that both of them are closely related and correspond to various types of fuzzy relation equations that are considered. Their relevance to the form of knowledge collected is also indicated. A problem of dimension reduction of a knowledge base is considered as well. Two modes of the use of the knowledge base (goal‐, and data‐driven) are also studied.

In the era of common digitalization and far reaching progress in the field of cybernetics, it is necessary to use the knowledge and experience in military cybernetics applications. In the field of machines, control fuzzy expert inference systems open new horizons and possibilities. Generally, the main affect of human efforts in the case of artificial intelligence is to create a machine with a set of behaviors and attitudes that would allow it to work independently, with ability to adjust to changing environmental conditions and an advisory role in the decision-making process. It should be noted that this technology used in some cases has already produced successful results. This paper aims to describe how the fuzzy expert inference membership function shapes influence analysis on selected air tasks efficiency evaluation results. Presented results prove that proper fuzzy membership functions shape selection has fundamental influence on aircraft system level of efficiency evaluation (its calculation accuracy). Using this technology in military aviation air tasks efficiency evaluation aspects is pioneer.

In the era of common digitalization and far reaching progress in the field of cybernetics, it is necessary to use the knowledge and experience in the domain of cybernetics in military applications. Artificial intelligence that so much influences on the imagination of scholars actually opens new horizons when it comes to control the machines. Relatively recently, it is introduced for military applications such departments of artificial intelligence as fuzzy logic, expert systems and fuzzy control theory.

In this paper, fuzzy expert inference membership function shapes influence analysis on selected air tasks efficiency evaluation results are described. Presented results prove that proper fuzzy membership functions shape selection has fundamental influence on aircraft system level of efficiency evaluation (its calculation accuracy).

The issue solved in the paper is based on application of theoretical results in practice. The paper can be estimated to bridge the gap between theory and practice in specific field.

Using this technology in military aviation air tasks efficiency evaluation aspects is pioneer.

The focus in ICT development has shifted from performance to maximization of tangibility. In particular, the interests in emotion-based services increase and more attention is paid to improving the quality of service and maximizing tangibility. Hence, it is necessary to model human emotions and utilize inferred emotions for services in order to enhance the quality of emotion-based personalized services. To this end, this study aims to model personalized emotional space by means of V-A emotion model and to suggest a fuzzy-based emotion inference method.

This study takes advantage of V-A emotion model, AHP and fuzzy integral technique to implement an emotion inference based on the quantitative evaluation and systematic expression of human emotions. By means of AHP, the personalized V-A emotion model was established. Fuzzy measure and Choquet integral methods were applied for emotion inference based on the inputs of valence and arousal (V-A) values, with the results evaluated in an experiment.

Thayer's emotion model structures 12 human emotions in reference to V-A values. This structure, however, may differ depending on individuals, and thus a method to measure and express it appropriately is necessary. This study evaluates the relative weight of 12 emotions based on AHP and regularizes them to compose the personalized V-A emotional space by drafting the V-A model. In addition, fuzzy integral-based emotion inference has been tested in reference to the V-A values on the established V-A emotion space.

Fuzzy integral-based emotion inference has been tested in reference to the V-A values on the established personalized emotion space.

Since imprecision, vagueness and ambiguity are often innate in human semantics, a flexible and tolerant method is needed to decode the voice of customer (VoC), so that the essential customer requirements can be identified and duly addressed. Quality function deployment (QFD) is a well‐known methodology for projecting the customer requirements onto the relevant design and production requirements and actions plan. This paper proposes an intelligent approach which extends the applications of QFD beyond its conventional boundary. The fuzzy inference technique is adopted to accommodate the possible imprecision and vagueness during VoC interpretation. The resulting model maps the customer requirements onto the relevant product attributes, taking into consideration their relationships and correlation during the inference process. The sub‐conclusions drawn from the fuzzy inference process are aggregated and defuzzified to yield the crisp design targets which can be used to guide the downstream manufacturing planning and control activities.

This paper addresses special reliability-centered maintenance (RCM) strategies for one-shot devices by providing fuzzy inferences system with the assumption that, to data, there is no data available on their maintenance. As far as one-shot devices are concerned, the relevant data is inadequate.

In this paper, a fuzzy expert system is proposed to effectively select RCM strategies for one-shot devices. In this research: (1) a human expert team is provided, (2) spatial RCM strategies for one-shot devices and parameters bearing upon those strategies are determined, (3) the verbal variables of the expert team are transformed into fuzzy sets, (4) the relationship between parameters and strategies are designed whereupon a model is developed by MATLAB software, (5) Finally, the model is applied to a real-life one-shot system.

The finding of this study indicates that the proposed fuzzy expert system can determine the parameters affecting the choice of the appropriate one-shot RCM strategies, and a fuzzy inference system can help for effective decision making.

The developed model can be used as a fast and reliable method for determining an appropriate one-shot RCM strategy, whose results can be relied upon with a suitable approximation in respect of the behavior test. To the best authors’ knowledge, this problem is not addressed yet.

The increasing complexity and dynamism of new technology implemented or to implement have imposed substantial uncertainties and subjectivities in the risk assessment process. This paper aims to present a risk assessment methodology for e-procurement implementation based on modified analytic network process (ANP) coupled with fuzzy inference systems.

ANP is modified in such a way that the experts can provide necessary data precise numerical value, a range of numerical values, a linguistic term or a fuzzy number. The proposed methodology incorporates knowledge and judgements obtained from experts to carry out identification of risk factors and to assess the risk magnitude of the identified risk factors based on factor index, risk likelihood and risk severity.

Risk magnitude of third party systems are found to be minor with a belief of 100 per cent, and for in-house systems, the risk is found to be between minor with a belief of 30 per cent and major of 70 per cent. The results indicate that by using the proposed methodology, the technological risk assessment of new technology can be done effectively and efficiently.

Using the results of this study, the practitioners can better know the pros and cons of implementing both in-house and third party e-procurement systems.

The modified ANP is used mainly to structure and prioritize the diverse risk factors. Finally, an illustrative example on technological risk assessment of both in-house and third party e-procurement systems is used to demonstrate the applicability of the proposed methodology in real life situations.

The paper aims to analyze the significance of key maintenance practices in effective implementation of the performance parameters in Northern Indian small and medium-sized enterprises (SMEs).

The present study deploys a fuzzy inference approach (fuzzy logic toolbox) to test the effective implementation of maintenance practices in SMEs. The significant maintenance factors are defined from applicable literature for this reason and validated by industry experts.

A model built into a fuzzy rule viewer and a surface view tool built into a fuzzy toolbox in MATLAB has highlighted the successful implementation of maintenance practices in Indian SMEs. The study highlights that corrective maintenance, general maintenance, preventive maintenance and breakdown maintenance problems have emerged as important indicator variables for effective synergistic implementation of maintenance practices in northern Indian SMEs.

An output assessment model is developed using a fuzzy set theory for maintenance practices, where performance evaluation is significant to the overall performance of SMEs.