Relevant bibliographies by topics / Fuzzy judgments

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Fuzzy judgments'

Author: Grafiati
Published: 30 May 2022
Last updated: 31 May 2022

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Journal articles on the topic "Fuzzy judgments"

1

Saaty, Thomas L., and Liem T. Tran. "Fuzzy Judgments and Fuzzy Sets." International Journal of Strategic Decision Sciences 1, no. 1 (January 2010): 23–40. http://dx.doi.org/10.4018/jsds.2010103002.

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Using fuzzy set theory has become attractive to many people. However, the many references cited here and in other works, little thought is given to why numbers should be made fuzzy before plunging into the necessary simulations to crank out numbers without giving reason or proof that it works to one’s advantage. In fact it does not often do that, certainly not in decision making. Regrettably, many published papers that use fuzzy set theory presumably to get better answers were not judged thoroughly by reviewers knowledgeable in both fuzzy theory and decision making. Buede and Maxwell (1995), who had done experiments on different ways of making decisions, found that fuzzy does the poorest job of obtaining the right decision as compared with other ways. “These experiments demonstrated that the MAVT (Multiattribute Value Theory) and AHP (Analytic Hierarchy Process) techniques, when provided with the same decision outcome data, very often identify the same alternatives as ‘best’. The other techniques are noticeably less consistent with the Fuzzy algorithm being the least consistent.”
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Posadsky, Alexey Igorevich, Tatiana Vladimirovna Sivakova, and Vladimir Anatolievich Sudakov. "Aggregation of Fuzzy Expert Judgments." Keldysh Institute Preprints, no. 101 (2019): 1–12. http://dx.doi.org/10.20948/prepr-2019-101.

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GHAZANFARI, MEHDI, and MAJID NOJAVAN. "EDUCING INCONSISTENCY IN FUZZY AHP BY MATHEMATICAL PROGRAMMING MODELS." Asia-Pacific Journal of Operational Research 21, no. 03 (September 2004): 379–91. http://dx.doi.org/10.1142/s0217595904000291.

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The inconsistency of judgments in the fuzzy Analytic Hierarchy Process (AHP) is a crucial issue. To make the appropriate decision, the inconsistency in decision maker's (DM) judgments needs to be eliminated or reduced. This paper proposes two mathematical models to deal with inconsistency in fuzzy AHP. In the first model, the DM's judgments are modified where the preference order of the DM's judgments remained unchanged. The second model allows reversing the preference orders of judgments. The proposed models aim to eliminate or reduce the inconsistency of fuzzy AHP by changing judgments. The models cause fewer changes for the high certain judgments. Two examples solved by the proposed models are included for purposes of illustration.
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Yang, Jing. "Synthesizing Different Preference Information by Fuzzy Programming Method." Advanced Materials Research 328-330 (September 2011): 2352–57. http://dx.doi.org/10.4028/www.scientific.net/amr.328-330.2352.

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Group decision making problems with different forms of preference information are discussed. Firstly, four forms of preference information ( i.e. preference ordering, utility value, AHP judgment matrix and fuzzy judgment matrix) are introduced and the computing formulas are given to transform different forms of preference information into the form of fuzzy judgment matrix. A new method that involves in different preference strength of experts is studied. Then, the assessment of the group priorities is formulated as a fuzzy linear programming problem, maximizing the group’s overall satisfaction to get the group solution. The method can easily deal with missing judgments and different partiality intensity by decision makers. At the end, the feasibility and effectiveness of method is explained by an example.
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Sudakov, V., and T. Sivakova. "Features of aggregation of fuzzy expert judgments." IOP Conference Series: Materials Science and Engineering 927 (September 26, 2020): 012034. http://dx.doi.org/10.1088/1757-899x/927/1/012034.

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6

Vicente, E., A. Mateos, and A. Jiménez-Martín. "A Betting- and Lottery-Based Method for Fuzzy Probability Elicitation." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 27, no. 01 (February 2019): 121–44. http://dx.doi.org/10.1142/s0218488519500065.

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It is very common to use linguistic term scales, whose terms are previously associated with different fuzzy numbers to assign probabilities to events in decision-making processes. However, the rigidity of such scales generates bias in the probability elicitation process and does not allow experts to adequately express their probabilistic judgments. We propose a betting and lottery-based method for eliciting a fuzzy number from the expert that represents his/her probabilistic judgments for a given event, along with a quality measure of the probabilistic judgments based on precision and consistency measures. We also enact a simulation process to analyze possible biases in the proposed fuzzy probability elicitation method.
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Simanihuruk, Tiarma, H. Hartono, Dahlan Abdullah, Cut Ita Erliana, Darmawan Napitupulu, Erianto Ongko, Robbi Rahim, Sukiman ., and Ansari Saleh Ahmar. "Hesitant Fuzzy Linguistic Term Sets with Fuzzy Grid Partition in Determining the Best Lecturer." International Journal of Engineering & Technology 7, no. 2.3 (March 8, 2018): 59. http://dx.doi.org/10.14419/ijet.v7i2.3.12322.

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Decision-making on conditions that involve many alternatives, many criteria, and many judgments is a difficult thing to do. The difficulty is coupled with assessors who sometimes make decisions in hesitant, unclear, and inconsistent circumstances and each person can provide different judgments. One of the methods that can be used is Hesitant Fuzzy Linguistic Term Sets which is the development of Fuzzy Sets that can make decisions by using Hesitant Fuzzy Sets. Hesitant linguistic term has been introduced for capturing the human way of reasoning using linguistic expressions involving different levels of precision. The integration of Hesitant Fuzzy Linguistic Term Sets with Fuzzy Grid Partition will enhance the ability in the decision making process. This research will discuss the use of Hesitant Fuzzy Linguistic Term Sets method and Fuzzy Grid Partition for best lecturers determination.
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Konyusheva, O. N. "FUZZY SYSTEMS BASED ON FUZZY LOGIC AND THEIR APPLICATION TO OPTIMIZATION PROBLEMS." SOFT MEASUREMENTS AND COMPUTING 1, no. 2 (2021): 50–64. http://dx.doi.org/10.36871/2618-9976.2021.02.005.

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Currently, fuzzy systems based on fuzzy logic are being implemented in all areas of human activity. The most relevant application of fuzzy set theory is in medicine, environmental protection, disaster protection, education, and many other fields for information processing, diagnostics, evaluation, forecasting, and modeling. This trend exists because of the main feature of fuzzy systems. It consists in the fact that in addition to objective laws, subjective representations and judgments of people play an essential role in their functioning. Almost all concepts in natural language and our knowledge in most areas are fuzzy. The ability of a person to make the right decisions in real situations containing a large number of uncertainties and inaccuracies requires the creation of a mathematical theory that would take into account and model the approximate judgments of a person.
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Yamashita, Toshiyuki. "Fuzzy Logical Approach to Perception of Dot Numerosity." Perceptual and Motor Skills 69, no. 3_suppl (December 1989): 1319–29. http://dx.doi.org/10.2466/pms.1989.69.3f.1319.

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The present study utilized a fuzzy logical approach for understanding human perception or judgments of dot numerosity. In Exp. 1 subjects were required to view dot patterns and to judge the truthfulness of the single and combined statements which asserted that the number of dots was large. The results indicated that (a) the rules based on the minimum and maximum truthfulness of the component statements best approximate subjective conjunction and disjunction about dot numerosity, when subjects kept the operations of the standard logic system in mind, (b) When the subjects based their judgments on perceptive impression, their judgments were best fitted by the multiplicative form.
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Yamashita, Toshiyuki. "Fuzzy Logical Approach to Perception of Dot Numerosity." Perceptual and Motor Skills 69, no. 3-2 (December 1989): 1319–29. http://dx.doi.org/10.1177/00315125890693-247.

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The present study utilized a fuzzy logical approach for understanding human perception or judgments of dot numerosity. In Exp. 1 subjects were required to view dot patterns and to judge the truthfulness of the single and combined statements which asserted that the number of dots was large. The results indicated that (a) the rules based on the minimum and maximum truthfulness of the component statements best approximate subjective conjunction and disjunction about dot numerosity, when subjects kept the operations of the standard logic system in mind. (b) When the subjects based their judgments on perceptive impression, their judgments were best fitted by the multiplicative form.
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Dissertations / Theses on the topic "Fuzzy judgments"

1

Кузьмін, Олексій Олегович, Дмитро Леонідович Орловський, and Андрій Михайлович Копп. "Оцінювання та аналіз навичок та компетенцій студентів ВНЗ." Thesis, Прикарпатський національний університет ім. Василя Стефаника, 2018. http://repository.kpi.kharkov.ua/handle/KhPI-Press/40857.

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У даній роботі розглянута задача нечіткого логічного висновку для прийняття рішень в задачах підбору контингенту студентів виходячи з вимог потенційних роботодавців, що дозволяє зменшити час на обробку інформації про кандидатів на конкретну посаду.
This paper considers the problem of the fuzzy logic inference in order to support the decision making procedure of students’ selection based on the requirements of the potential employers. This approach allows reducing the time spent on the processing of the information about candidates for a certain position. The fuzzy characteristics of the input data set are implemented, the set of fuzzy logic inference rules is defined, the algorithm of fuzzy logic inference, which allows selecting students that better suite for a certain competence, is outlined. For the example we have considered the problem of selection of the best candidate for the position “Junior Front-End Developer” among the set of four sample candidates. By using the set of required skills in the field of front-end web development, we have applied the proposed approach to estimate the scores of such skills for each candidate in order to pick the candidates with the best score.
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Maloney, Krisellen 1960. "Information representation for judgment and decision-making in the development of expertise in radiology: A fuzzy-trace theory analysis." Diss., The University of Arizona, 1998. http://hdl.handle.net/10150/288847.

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Traditional information-processing accounts of the reasoning process in radiology assume that humans process the details of the input image in order to compute judgments. In these accounts, the development of expertise involves the acquisition of increasingly precise and complex internal problem representations that are based on a normal anatomy prototype. Fuzzy-trace theory predicts that accurate judgments rely on the reasoners ability to ignore irrelevant detail, to retrieve relevant gist memories and to accurately instantiate the image information with respect to the internal representation. Fuzzy-trace theory predicts that the development of expertise involves the ability to access and process less precise and complex internal representations (i.e., gist). The purpose of this study was to examine the internal representations used to make judgments in radiology and to quantify the changes in complexity of the internal representations, as well as the differences in time, accuracy and confidence that might be associated with experience. Thirty-five subjects from general and specialized expertise samples participated. Each subject was presented with 32 chest films including normal films, films with precise disease patterns (mass category) and diffuse disease patterns (interstitial and airspace category). For each film, the participant made a series of judgments (normal/abnormal; category; specific diagnosis) and then sketched the features that were essential to the judgments. The information content and complexity of the representations were calculated using an approach that considered the underlying meaning of the sketches rather than the surface form. The sketches were converted to propositions and the information in the propositions was evaluated in terms of possible world semantics. Time, accuracy, confidence and content measures supported the prediction of fuzzy-trace theory that the internal representations are abnormality-based. Consistent with predictions regarding the acquisition and use of gist representations expertise was associated with greater improvements in accuracy for interstitial (as opposed to mass) films; accuracy was higher with interstitial films when judgments were less reliant on surface detail (normal/abnormal); and accuracy was higher for mass films when judgments were more reliant on surface detail (specific diagnosis). Complexity measures showed that the overall representations did not get more complex with the development of expertise.
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Rubinchik, Nataliya. "A demonstration of the meta-studies methodology using the risky-choice framing effect." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1574201911927335.

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Недашківська, Надія Іванівна. "Методологія та інструментарій підтримки прийняття рішень на основі ієрархічних та мережевих моделей." Thesis, КПІ ім. Ігоря Сікорського, 2018. https://ela.kpi.ua/handle/123456789/25122.

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Робота виконана в Інституті прикладного системного аналізу Національного технічного університету України «Київський політехнічний інститут імені Ігоря Сікорського»
У дисертаційній роботі запропоновано методологію підтримки прийняття рішень, яка з використанням розробленого системного підходу дозволяє підвищити достовірність розв’язків в складних слабко структурованих системах на основі ієрархічних та мережевих моделей і включає нові та удосконалені методи: оцінювання і підвищення узгодженості матриць парних порівнянь загального виду залежно від властивостей цих матриць, розрахунку довірчих інтервалів для локальних ваг, розрахунку нечітких локальних ваг, гібридний метод розрахунку локальних та агрегованих ваг, метод комплексного оцінювання чутливості розв'язку та спосіб оцінювання реверсу рангів при використанні різних правил комбінування функцій довіри. Розроблено нові методики, засоби та система моделювання експертного оцінювання. Практичне значення одержаних результатів полягає у створенні інструментарію у вигляді системи підтримки прийняття рішень, який застосовано при розв'язанні практичних задач на замовлення міністерств і відомств України.
In the dissertation work, an important scientific and technical problem has been solved, which deals with development of mathematical and methodological support for increasing the reliability of solutions to decision analysis problems in complex weakly structured systems based on hierarchical and network models. The scientific novelty of the work is determined by the following theoretical and practical results obtained by author. Using proposed systematic approach, a new methodology of decision support is developed, which allows to increase the reliability of solutions of decision analysis problems in complex weakly structured systems on the basis of hierarchical and network models. This methodology includes the proposed and described below methods and techniques. A new method for evaluating and improving the consistency of expert judgements, which are given in a form of pairwise comparison matrix, is developed. Features of the method include an analysis of property of weak inconsistency, the presence of cycles in a pairwise comparison matrix and a search for the most inconsistent element of this matrix. The method can be applied to pairwise comparison matrices of various types, including multiplicative, additive, fuzzy and other. A Transitiv method for searching the most inconsistent elements of the matrix is proposed. A method of flows for finding the most inconsistent element of the matrix is improved by taking into account the input flow. The simulation shows that the developed Transitiv method and the method of flows are more efficient than existing methods. Usage of the proposed method of consistency evaluating and improving allows to obtain pairwise comparison matrices of acceptable quality for all elements of the model and these matrices can be used further to find local weights of model’s elements. A new method for calculating confidence intervals of local weights is developed, which, unlike others, takes into account the uncertainty of scale, expert's personal qualities such as optimism and pessimism, and does not require comparison of groups of elements with the frame. The method is based on notions of the Dempster-Schafer theory of evidence and results of computer simulation of expert's judgments. An uncertainty index of expert judgments is proposed, assuming that this uncertainty is caused by above factors. An improved method for calculating fuzzy local weights on basis of fuzzy pairwise comparison matrix is proposed, which differs from others in estimating and increasing the consistency of the matrix and taking into account properties of weak and strong order preservation on a set of calculated fuzzy weights. This method, unlike existing ones, makes it possible to determine the weak inconsistency of fuzzy matrix, to assess the acceptability of inconsistency level of fuzzy matrix for reliable local weights calculation, and to find the most inconsistent elements of the matrix using methods developed for crisp matrices. A hybrid method for calculating aggregated weights of hierarchical model elements with interdependent decision criteria has been improved, when input data for evaluation are fuzzy expert judgments. Improvement consists in using the developed more effective methods for assessment and increasing of crisp and fuzzy expert judgements consistency. A method for complex sensitivity analysis of results has been improved by taking into account sensitivity analysis of local rankings of model’s elements. In the developed method for estimating local sensitivity, intervals and indices of stability of pairwise comparison matrix elements are calculated, which retain the best decision alternative and all ranking of alternatives. Resulting stability intervals allow to find critical elements of the problem that require more careful analysis. A new technique for estimating the rank reversal is suggested, which can appear after applying combination rules of confidence functions for model’s elements. Using this technique, the Dempster, Yager, Zhang, Dubois and Prada and other combination rules were examined. Cases and features of rank reversals appearance in these rules were revealed. New techniques and tools for modeling a process of decision alternatives evaluation by an expert of high competence, expert-optimist and expert-pessimist while performing pairwise comparisons are developed. Using these techniques and tools, efficiency of proposed methods has been proved. A decision support system has been constructed on basis of proposed methods and techniques. This system has been used to solve several practical problems. Within the work with the Ministry of Education and Science of Ukraine, critical technologies of the Ukrainian energy industry were assessed, priorities of technologies were calculated and aggregated according to hierarchical model of criteria, and on their basis the most priority technologies for implementation were identified. In the course of research work together with the Institute of Space Research, directions of the expedient use of space information for remote sensing of the Earth for geoinformation systems were evaluated and the relative demand for the space information in the national economy of Ukraine was determined. On order of the Kyiv City State Administration, social problems of the Kyiv city were estimated in terms of benefits, costs, opportunities and risks, followed by selection of priority activities for implementation and evaluation of scenarios of the transport system development. Results of the dissertation work have been introduced into the educational process of the department "Mathematical methods of system analysis" of Institute for applied system analysis of National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”.
В диссертационной работе предложена методология поддержки принятия решений, которая с использованием разработанного системного подхода позволяет повысить достоверность решений в сложных слабо структурированных системах на основе иерархических и сетевых моделей и включает новые и усовершенствованные методы: оценки и повышения согласованности матриц парных сравнений общего вида в зависимости от свойств этих матриц, расчета доверительных интервалов для локальных весов, расчета нечетких локальных весов, гибридный метод расчета локальных и агрегированных весов, метод комплексной оценки чувствительности решения, а также способ оценки реверса рангов при использовании различных правил комбинирования функций доверия. Разработаны новые методики, средства и система моделирования экспертного оценивания. Практическое значение полученных результатов заключается в создании инструментария в виде системы поддержки принятия решений, который применен при решении практических задач по заказу министерств и ведомств Украины.
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5

Недашківська, Надія Іванівна. "Методологія та інструментарій підтримки прийняття рішень на основі ієрархічних та мережевих моделей." Doctoral thesis, Київ, 2018. https://ela.kpi.ua/handle/123456789/25119.

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Робота виконана в Інституті прикладного системного аналізу Національного технічного університету України «Київський політехнічний інститут імені Ігоря Сікорського»
У дисертаційній роботі запропоновано методологію підтримки прийняття рішень, яка з використанням розробленого системного підходу дозволяє підвищити достовірність розв’язків в складних слабко структурованих системах на основі ієрархічних та мережевих моделей і включає нові та удосконалені методи: оцінювання і підвищення узгодженості матриць парних порівнянь загального виду залежно від властивостей цих матриць, розрахунку довірчих інтервалів для локальних ваг, розрахунку нечітких локальних ваг, гібридний метод розрахунку локальних та агрегованих ваг, метод комплексного оцінювання чутливості розв'язку та спосіб оцінювання реверсу рангів при використанні різних правил комбінування функцій довіри. Розроблено нові методики, засоби та система моделювання експертного оцінювання. Практичне значення одержаних результатів полягає у створенні інструментарію у вигляді системи підтримки прийняття рішень, який застосовано при розв'язанні практичних задач на замовлення міністерств і відомств України.
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Jhou, Yu-Kai, and 周煜凱. "Decomposed Fuzzy Controller and Machine Vision Applied to Direction Judgment and Assembling Mechanism." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/07159339193637326666.

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碩士
龍華科技大學
機械工程系碩士班
103
The paper applies decomposed Fuzzy Controller and Machine Vision to Direction Judgment and Assembling Mechanism. Adapted mechanism is a B degree mechatronics test device defined by Skill Evaluation Center of workforce development agency, ministry of labor. Parts of device are modified: direction judgment sensor replaced by machine vision, PLC control replaced by PC-Based control, step motor replaced by induction motor and LABVIEW software designed program, Machine vision judges the grooves direction of the workpiece. The method of image processing has gray level, edge detection and pattern matching , Experiment results show image identification is effective. And then use decomposed fuzzy system (DFS) PID controller for motor positioning. The DFS structure is to decompose each fuzzy variable into layers of fuzzy systems, and each layer is to characterize one traditional fuzzy set. Similar to forming fuzzy rules in traditional fuzzy system, layers from different variables form the so-called component fuzzy systems. First, using LabVIEW, simulate motor positioning with traditional fuzzy, three layers DFS, and nine layers DFS. Simulation results show no obvious difference. Experimental results show the settling time of nine layers DFS is better than others. Finally, according B degree mechatronics test device process, assemble workpieces.
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Ou, Tsung-Lin, and 歐宗霖. "Implementing“Clustering with scale” in Item Scoring:The Development and Application of Fuzzy Scoring on Situational Judgment Tests." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/7z5bfy.

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博士
國立中央大學
企業管理學系
105
Based on the viewpoints of Fuzzy theory, the aim of this research is to deal with judgment uncertainty which was ignored on the issue of scoring situational judgment test. By the literature inference, the research developed the approach of Situational Judgment Test Fuzzy Scoring and take the pick-best scale of situational judgment test as a demonstration, adapting simulated and empirical research to compare the differences between the fuzzy scoring and the crisp scoring. Analysis of results concludes that: (1) Situational Judgment Test Fuzzy Scoring can integrate the information of forced and unforced response of a subject to deal with uncertainty on judgment process. (2) Situational Judgment Test Fuzzy Scoring can consider the class of grouping and the individual disparity together to strengthen the efficacy of employee selection. Finally, practical and academic viewpoints about fuzzy scoring on Situational Judgment Test were discussed for the future study.
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Maloney, Krisellen. "Information Representation for Judgment and Decision-Making in the Development of Expertise in Radiology: A Fuzzy-Trace Theory Analysis." Thesis, 1998. http://hdl.handle.net/10150/105656.

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Traditional information-processing accounts of the reasoning process in radiology assume that humans process the details of the input image in order to compute judgments. In these accounts, the development of expertise involves the acquisition of increasingly precise and complex internal problem representations that are based on a normal anatomy prototype. Fuzzy-trace theory predicts that accurate judgments rely on the reasoners ability to ignore irrelevant detail, to retrieve relevant gist memories and to accurately instantiate the image information with respect to the internal representation. Fuzzy-trace theory predicts that the development of expertise involves the ability to access and process less precise and complex internal representations (i.e., gist). The purpose of this study was to examine the internal representations used to make judgments in radiology and to quantify the changes in complexity of the internal representations, as well as the differences in time, accuracy and confidence that might be associated with experience. Thirty-five subjects from general and specialized expertise samples participated. Each subject was presented with 32 chest films including normal films, films with precise disease patterns (mass category) and diffuse disease patterns (interstitial and airspace category) . For each film, the participant made a series of judgments (normal/abnormal; category; specific diagnosis) and then sketched the features that were essential to the judgments.
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Books on the topic "Fuzzy judgments"

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Dongrui, Wu, ed. Perceptual computing: Aiding people in making subjective judgments. Piscataway, NJ: IEEE Press, 2010.

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Effer-Uhe, Daniel Oliver. Die Bindungswirkung von Präjudizien: Eine Untersuchung aus dem Blickwinkel von Prinzipientheorie und Fuzzy-Logik. Göttingen: Cuvillier, 2008.

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Mendel, Jerry M. Perceptual computing: Aiding people in making subjective judgments. Hoboken, N.J: John Wiley & Sons, 2010.

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Mendel, Jerry, and Dongrui Wu. Perceptual Computing: Aiding People in Making Subjective Judgments. Wiley & Sons, Incorporated, John, 2010.

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Book chapters on the topic "Fuzzy judgments"

1

Smithson, Michael. "A Class of Fuzzy Featural Models of Similarity Judgments." In Fuzzy Logic, 377–84. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-2014-2_35.

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Nakamura, Kazuo. "On the Nature of Intransitivity in Human Preferential Judgments." In Fuzzy Approach to Reasoning and Decision-Making, 147–62. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2753-0_13.

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Mendel, Jerry M., Sheila Murphy, Lynn C. Miller, Matt Martin, and Nilesh Karnik. "The Fuzzy Logic Advisor for Social Judgments: A First Attempt." In Computing with Words in Information/Intelligent Systems 2, 459–83. Heidelberg: Physica-Verlag HD, 1999. http://dx.doi.org/10.1007/978-3-7908-1872-7_22.

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Mete, Suleyman, Nurdan Ece Oz, Muhammet Gul, Faruk Serin, and Erkan Celik. "A Risk Assessment Approach Using Both Stochastic Data and Subjective Judgments." In Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making, 1104–11. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23756-1_130.

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Li, Zongmin, Ye Zhao, and Asaf Hajiyev. "Multi-criteria Evaluation of Rumor Refuting Platform’s Refuting Capacity with Hesitant Fuzzy Judgments." In Proceedings of the Fifteenth International Conference on Management Science and Engineering Management, 46–57. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79203-9_5.

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Kacprzyk, Janusz. "Bipolar Models for a More Realistic Representation and Processing of Human Judgments, Intentions and Preferences: A Role of Fuzzy Logic." In Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making, 3. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23756-1_1.

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Ji, Wen, Haoshan Shi, and Ying Wang. "Objective Evaluation for Compressed Video Quality Based on Fuzzy Synthetic Judgment." In Fuzzy Systems and Knowledge Discovery, 753–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11881599_92.

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Zhang, Qian, Jianxia Chen, Fan Yang, Yu Cheng, and Liang Xiao. "A Novel Approach of Automatic Judgment for Subjective Questions." In Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery, 341–47. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70665-4_40.

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Yeh, Chung-Hsing, and Yu-Hern Chang. "Optimizing Relative Weights of Alternatives with Fuzzy Comparative Judgment." In Computational Science and Its Applications - ICCSA 2006, 649–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11751595_69.

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Cannavacciuolo, A., G. Capaldo, A. Ventre, A. Volpe, and G. Zollo. "The Representation of Human Judgment by Using Fuzzy Techniques." In ICANN ’94, 193–96. London: Springer London, 1994. http://dx.doi.org/10.1007/978-1-4471-2097-1_45.

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Conference papers on the topic "Fuzzy judgments"

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Sule, Dileep R., Tory K. Watkins, and David Restifo. "Fuzzy Logic Application in Data Acquisition." In ASME 2001 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/detc2001/cie-21250.

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Abstract The aim of this paper is to introduce an expansion of the practice of using surveys when making subjective judgments or decisions. This method is particularly useful in situations in which precise data is limited or nonexistent. It can be especially valuable when working with new designs by reducing the error associated with estimates in the beginning of the product’s life cycle in which costs are greatest. Our approach modifies the traditional survey style by including fuzzy logic and expert judgment. Using fuzzy logic, we solicit the information in a way that gives the evaluator a continuous choice for the cost estimate and a method to indicate the level of confidence in a linguistic manner. By doing this, a range of the likely values for the real value can be defined, and a subjective judgment can be turned into objective information that can be more useful than the traditional approach.
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Entani, Tomoe. "Fuzzy Approach for Group Assessment Based on the Consistency of Individual Judgments." In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2019. http://dx.doi.org/10.1109/fuzz-ieee.2019.8858897.

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Rodrigues, Matilde A., Celina P. Leão, Eusébio Nunes, Sérgio Sousa, and Pedro Arezes. "The Application of a Fuzzy Approach to the Analysis of OSH Practitioners Level of Risk Acceptance." In ASME 2014 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/imece2014-40069.

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Organizations need constantly to take decisions about risk. In this process, Occupational Safety & Health (OSH) practitioners’ judgments have a great importance. If on one hand they have the technical knowledge about risk, on the other hand the decisions can be dependent on their level of risk acceptance. In view of this, this paper analyzes the views of the OSH practitioners about the level of risk acceptance, using the Fuzzy logic approach. A questionnaire to the analysis of the reported level of risk acceptance was developed and applied. The questionnaire included 79 risk scenarios, each accounted for the frequency of an accident with more lost workdays than a given magnitude. Through the two-step cluster analysis three groups of OSH practitioners were identified: Unacceptable, Tolerable and Realistic groups. A further analysis of the realistic group judgments about risk was performed, using the Fuzzy logic approach. The fuzzy sets of inputs and output variables were determined and the relationship between the variables was mapped through fuzzy rules. After that, the Min–Max fuzzy inference method was used. The obtained results show that the risk level is acceptable when input variables are at the lowest value and unacceptable when the risk level is high. Furthermore, the results obtained allow to better understand the uncertainty related with the OSH practitioners judgments being an important step to better understand the modeling of judgments about risk acceptance level allowing to know the different risk acceptance levels for the different accident scenarios.
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Li, Junhong, Mingjuan Dong, Fengchun Zhang, and Liyu Nie. "Group priority vector based on comparison judgments." In 2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2011). IEEE, 2011. http://dx.doi.org/10.1109/fskd.2011.6019499.

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Chen, Zhong-Zhe, Yu Liu, Hong-Zhong Huang, Dan Ling, and Li-Ping He. "A Fuzzy Similarity-Based Approach to Reliability Allocation of Diesel Engine." In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-47378.

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Most of new products evolve based upon existing products. The reliability indices and maintenance records of existing products are very important to provide useful information for the reliability allocation of the new evolutionary products. In this paper, a fuzzy similarity-based reliability allocation method which considers not only the similarity between the new product and old ones, but also the judgments from domain experts, is proposed to realize a reasonable reliability allocation at the initial design stage of diesel engines. The new method allows for using both the objective information from the old products and the subjective judgments from experts simultaneously, and it is more comprehensive and objective compared to the traditional reliability allocation method.
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Kunsch, P. L. "A Framework for Assessing the Cost and Financing Uncertainties of the Belgian High Level-Waste Repository." In ASME 2003 9th International Conference on Radioactive Waste Management and Environmental Remediation. ASMEDC, 2003. http://dx.doi.org/10.1115/icem2003-4636.

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This paper presents the general approach presently developed by ONDRAF/NIRAS/NERAS, the Belgian radioactive waste management agency for dealing with the economic and financial uncertainties of the High-level-Waste (HLW) repository project in clay. This project will be for many more years the object of R&D studies. Many uncertainties thus still exist regarding the final design, the eventual costs, and the realisation schedule. Recommendations from the Electric Power Research Institute (EPRI) are available for computing contingency factors to be applied on top of the basic costs delivered by project engineers. We show in this paper that fuzzy logic is a natural way to use the recommendations of EPRI. Fuzzy logic is a mathematical technique for representing unprecise or relatively vague judgments made by experts, like: ‘this project is preliminary’, ‘this concept is insufficiently mature’, etc. This approach is considered in many fields as being well-suited for coping with uncertainties implied by such judgments. In the present case, distinction is made between uncertainties related to policy, project, technology, and realisation schedule. The paper details the sequence of basic steps used by the agency to produce as a final product the per-unit tariff of the different waste categories. Expert judgments are interpreted by the fuzzy-logic technique to derive EPRI-like contingency factors for each project task, as well as a fuzzy operating schedule within a given political scenario. Conclusions are given on how this approach can be validated and set into practice.
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Musharraf, Mashrura, Faisal Khan, Brian Veitch, Scott MacKinnon, and Syed Imtiaz. "Human Factor Risk Assessment During Emergency Condition in Harsh Environment." In ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/omae2013-10867.

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This paper presents a quantitative approach to human factors risk analysis during emergency conditions on an offshore petroleum facility located in a harsh environment. Due to the lack of human factors data for emergency conditions, most of the available human factors risk assessment methodologies are based on expert judgment techniques. Expert judgment is a valuable technique, however, it suffers from vagueness, subjectivity and incompleteness due to a lack of supporting empirical evidence. These weaknesses are often not accounted for in conventional human factors risk assessment. The available approaches also suffer from the unrealistic assumption of independence of the human performance shaping (HPS) factors and actions. The focus of this paper is to address the issue of handling uncertainty associated with expert judgments and to account for the dependency among the HPS factors and actions. These outcomes are achieved by integrating Bayesian Networks with Fuzzy and Evidence theories to estimate human error probabilities during different phases of an emergency. To test the applicability of the approach, results are compared with an analytical approach. The study demonstrates that the proposed approach is effective in assessing human error probability, which in turn improves reliability and auditability of human factors risk assessment.
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Chen, Xia, and Li-Hong Ma. "An Analytic Method for Consensus Analysis in Group Experts' Judgments Based on Numerical Decision Matrix Preference Information." In 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). IEEE, 2008. http://dx.doi.org/10.1109/fskd.2008.502.

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Nguyen, Hoang. "Atanassov's intuitionistic fuzzy risk estimation of the ship system failures based on the expert judgments." In 2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA). IEEE, 2017. http://dx.doi.org/10.1109/inista.2017.8001153.

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Zhou, Jiao, Xingyu Peng, and Dongchi Yao. "Quantitative Risk Assessment Techniques Based on Uncertainty Theory for Natural Gas Distribution Station." In 2018 12th International Pipeline Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/ipc2018-78260.

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Pipeline stations, as an important part of long-distance pipeline systems, include lots of facilities which are highly concentrated and always operate continuously. Risk assessment is an important foundation work for the risk management of these stations. Since various uncertainties exist during the quantitative risk assessment (QRA), this paper explores the theories and approaches of QRA for station accidents, and also introduces some specific mathematical theories for quantification and dealing with uncertainties. This paper combines uncertainty theory effectively with the QRA for gas distribution stations, analyzes the uncertain factors in the QRA of gas distribution station, and establishes Bayesian update model for estimating basic events’ failure rates and probabilities of failure on demand based on generic failure data and plant-specific data. And it also offers conversion method among conjugate prior distribution of different types. Besides, probabilistic estimation model is set up by the combination of fuzzy set theory, expert judgments and fuzzy group decision making. The paper builds Fuzzy Bow-Tie quantitative model for distribution station under dependency relationships, and proposes the sensitivity analysis method for the accident model based on fuzzy importance index, fuzzy uncertainty index and minimal cut sets importance index.
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