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Опубліковано: 11 вересня 2023

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Статті в журналах з теми "FUZZY BASED APPROACH"

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JENA, KALYAN KUMAR, SASMITA MISHRA, SAROJANANDA MISHRA, SOURAV KUMAR BHOI, and SOUMYA RANJAN NAYAK. "MRI Brain Tumor Image Analysis Using Fuzzy Rule based Approach." Journal of Research on the Lepidoptera 50, no. 2 (June 25, 2019): 98–112. http://dx.doi.org/10.36872/lepi/v50i2/201012.

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Mama, Rachid, and Mustapha Machkour. "Fuzzy querying with SQL: Fuzzy view-based approach." Journal of Intelligent & Fuzzy Systems 40, no. 5 (April 22, 2021): 9937–48. http://dx.doi.org/10.3233/jifs-202551.

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Nowadays several works have been proposed that allow users to perform fuzzy queries on relational databases. But most of these systems based on an additional software layer to translate a fuzzy query and a supplementary layer of a classic database management system (DBMS) to evaluate fuzzy predicates, which induces an important overhead. They are not also easy to implement by a non-expert user. Here we have proposed a simple and intelligent approach to extend the SQL language to allow us to write flexible conditions in our queries without the need for translation. The main idea is to use a view to manipulate the satisfaction degrees related to user-defined fuzzy predicates, instead of calculating them at runtime employing user functions embedded in the query. Consequently, the response time of executing a fuzzy query statement will be reduced. This approach allows us to easily integrate most fuzzy request characters such as fuzzy modifiers, fuzzy quantifiers, fuzzy joins, etc. Moreover, we present a user-friendly interface to make it easy to use fuzzy linguistic values in all clauses of a select statement. The main contribution of this paper is to accelerate the execution of fuzzy query statements.
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Chandra, Vishal, and Savita Shiwani. "Fuzzy based Effort Estimation Approach." International Journal of Computer Applications 103, no. 17 (October 18, 2014): 39–42. http://dx.doi.org/10.5120/18305-9438.

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4

Abuhijleh, Eman A., Mourad Massa’deh, Amani Sheimat, and Abdulazeez Alkouri. "Complex Fuzzy Groups Based on Rosenfeld’s Approach." WSEAS TRANSACTIONS ON MATHEMATICS 20 (August 4, 2021): 368–77. http://dx.doi.org/10.37394/23206.2021.20.38.

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Complex fuzzy sets (CFS) generalize traditional fuzzy sets (FS) since the membership functions of CFS reduces to the membership functions of FS. FS values are always at [0, 1], unlike CFS which has values in the unit disk of C. This paper merges notion and concept in group theory and presents the notion of a complex fuzzy subgroup of a group. This proposed idea represents a more general and better optional mathematical tool as one of the approaches in the fuzzy group. However, this research defines the notion of complex fuzzy subgroupiod, complex fuzzy normal subgroup, and complex fuzzy left(right) ideal. Therefore, the lattice, homomorphic preimage, and image of complex fuzzy subgroupiod and ideal are introduced and studied its properties. Finally, complex fuzzy subgroups and their properties are presented and investigated
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., Malkhan. "Fuzzy Logic Based Approach for Analysis and Synthesis of Failure Modes." Journal of Advanced Research in Production and Industrial Engineering 8, no. 1&2 (April 19, 2021): 18–22. http://dx.doi.org/10.24321/2456.429x.202102.

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Failure analysis and management has been gaining a lot of importance for the last few years. Failure mode and effect analysis is the process used for failure analysis and risk management in judging various businesses and managements. The FMEA is the methodology extensively used in different sectors to detect, prioritize and investigate the potential failures which occur during the production or design of the product. This whole process is computed with the Risk Priority Number (RPN). The blurriness and uncertainty in the FMEA associated with the human expertise and experience is responded using Fuzzy Logic based approach. In today’s time, organizations mainly focus on improving the quality of their product and building the reputation of their organizations. So, they consider every aspect of failure which can occur during the production. So, they use the FMEA team to overcome these issues before their existence. This paper is based on the approach of FMEA methodology and Fuzzy logic which describes multiple risks, insecurities associated with the different production processes and gives the solution to overcome the possible failures. FMEA is a methodology which suggests that such type of failures could occur during the design of the product or the production of the product.
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Zarinbal, M., and M. H. Fazel Zarandi. "Type-2 fuzzy image enhancement: Fuzzy rule based approach." Journal of Intelligent & Fuzzy Systems 26, no. 5 (2014): 2291–301. http://dx.doi.org/10.3233/ifs-130902.

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Watanabe, Toshihiko, and Hirosato Seki. "Modeling Approach Based on Modular Fuzzy Model." Journal of Advanced Computational Intelligence and Intelligent Informatics 16, no. 5 (July 20, 2012): 653–61. http://dx.doi.org/10.20965/jaciii.2012.p0653.

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Fuzzy modeling is one of the most important techniques for nonlinear modeling. SIRMs (Single Input Rule Modules) has been studied as a useful modeling method for real-life applications such as control and pattern recognition. Although the SIRMs is a practical modeling approach based on fuzzy reasoning, its performance is adversely affected by high-dimensional or complicated characteristics of the problems. The modular fuzzy model is an extension of the SIRMs for overcoming such a performance problem. In this paper, we study a modeling approach based on the modular fuzzy model by extending the SIRMs architecture. We show that the construction of error objective functions for modeling the modular fuzzy model and the SIRMs affects the prediction performance of the model. Through numerical experiments on modeling problems and reinforcement learning problems, we study the model construction based on the error objective functions. We find that the error objective function should be selected according to the number of dimensions of projection in the modular fuzzy model.
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EFE, Burak. "An integrated fuzzy approach based failure mode and effects analysis for a risk assessment." Bitlis Eren Üniversitesi Fen Bilimleri Dergisi 11, no. 2 (June 30, 2022): 681–96. http://dx.doi.org/10.17798/bitlisfen.1088988.

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This paper provides to cope with the limitations of traditional FMEA by using an integrated fuzzy multi-criteria decision making method, which considers fuzzy extension of AHP (Analytic Hierarchy Process) and fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), and a linear programming. The proposed method is shown for an application to failure mode and effects analysis (FMEA) based risk assessment of a construction firm. Firstly, fuzzy extension of AHP approach is utilized to define the weights of criteria in risk evaluation. Secondly, fuzzy TOPSIS approach is used to determine the most important failure mode in the construction firm. This work handles a sensitivity analysis and a comparison with the other methods. FMEA related papers in the literature presents only ranking of failure modes by using various methods. This study aims to handle the limited resources such as budget and time in a linear programming to establish a suitable occupational health and safety policy.
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Shyi-Ming Chen. "A fuzzy reasoning approach for rule-based systems based on fuzzy logics." IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics) 26, no. 5 (1996): 769–78. http://dx.doi.org/10.1109/3477.537318.

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ÖZTÜRK, Müslüm, Belkız TORĞUL, and Turan PAKSOY. "Sürdürülebilir Tedarikçi Seçimi için Aralık Tip-2 Bulanık Kural Tabanlı BWM Yaklaşımı." Konya Journal of Engineering Sciences 10, no. 2 (June 1, 2022): 312–36. http://dx.doi.org/10.36306/konjes.991295.

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Анотація:
Fuzzy logic is a theory based on human-specific approximate reasoning. Therefore, fuzzy logic applications can bring simple and more effective solutions to situations that classical methods cannot overcome. The type-1 fuzzy set is a set, which has a continuous (crisp) membership degree to which a membership degree between 0 and 1 is assigned, and is characterised by membership functions. Type-2 fuzzy sets, which have the power to express uncertainty better, are expressed by membership functions, where the membership degrees of each element belonging to that set also specify a fuzzy set.Therefore, type-2 fuzzy sets allow us to include the membership functions uncertainty in fuzzy set theory. Using expert knowledge and using sensitivity of human to reflect the level of the decision maker influence is expressed as a fuzzy rule based system. Recently, it has been seen that fuzzy rules are frequently used together with multi-criteria decision making (MCDM) methods. Again, combining fuzzy rules with type-2 fuzzy numbers is also found. In this study, the Best Worst Method (BWM), one of the MCDM methods, has been integrated with fuzzy rules based interval type-2. The developed hybrid method was defined as Interval Type-2 Fuzzy Rule-Based BWM (IT2 FRB BWM). The proposed hybrid method has an important place when there are alternatives with similar ranking positions. Thus, even if there is a small difference in each alternative, it will show the difference better (more sensitively). This makes the proposed hybrid method forceful and unique.The proposed approach has been applied to a sustainable supplier selection problem comparatively with the BWM. The results show that the IT2 FRB BWM approach is more successful in ordering alternatives than the classical BWM method.
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Дисертації з теми "FUZZY BASED APPROACH"

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Mac, Connell Peter Frederick Andrew. "Heating control using a knowledge-based approach." Thesis, University of Exeter, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.296234.

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Dan, Qing. "A fuzzy rule-based approach for edge feature classification." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/MQ39646.pdf.

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Osut, Demet. "A Behavior Based Robot Control System Using Neuro-fuzzy Approach." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/109765/index.pdf.

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In autonomous navigation of mobile robots the dynamic environment is a source of problems. Because it is not possible to model all the possible conditions, the key point in the robot control is to design a system that is adaptable to different conditions and robust in dynamic environments. This study presents a reactive control system for a Khepera robot with the ability to navigate in a dynamic environment for reaching goal objects. The main motivation of this research is to design a robot control, which is robust to sensor errors and sudden changes and adaptable to different environments and conditions. Behavior based approach is used with taking the advantage of fuzzy reasoning in design. Experiments are made on Webots, which is a simulation environment for Khepera robot.
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OLIVEIRA, CARLOS ALEXANDRE DOS SANTOS. "STRATEGIC GROUPS: ARESOURCE-BASED VIEW AND NEURO-FUZZY SYSTEMS APPROACH." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2004. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=5856@1.

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Анотація:
PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
Desde sua formulação, no início da década de setenta, o conceito de grupo estratégico é objeto de pesquisas teóricas e empíricas que buscam confirmar sua existência, sua contribuição à avaliação da performance e à formação das estratégias das empresas. Este trabalho soma-se a estas pesquisas, utilizando os conceitos da Visão Resource- Based e a aplicação de ferramentas de inteligência computacional, neste caso as redes neurais e os sistemas de inferência fuzzy, com o objetivo de contribuir para a discussão deste tema na superação de suas limitações e dos novos desafios que o aumento da complexidade das arenas competitivas trouxeram para as pesquisas do gerenciamento estratégico. A Visão Resource-Based fornece a base teórica para o desenvolvimento dos construtos: grau de inimitabilidade e grau de imobilidade, resultantes da exploração estratégica dos recursos da empresa. Estes construtos são propostos como dimensões de avaliação da semelhança estratégica entre as empresas de uma arena competitiva. A inteligência computacional fornece os meios de extração de informações subjetivas, e presentes em ambientes complexos, através da simulação do aprendizado, percepção, evolução e adaptação do raciocínio humano. O resultado é a proposição de um modelo de avaliação da existência de grupos estratégicos, utilizando os construtos Grau de Inimitabilidade e Grau de Imobilidade, e Sistemas Neuro-fuzzy. Este modelo é aplicado ao setor de supermercados como teste de validação do mesmo.
Since its has introduced, in the beginning of the decade of seventy, the concept of strategic groups is object of theoretical and empirical research that aims to confirm its existence, its contribution to performance evaluation and the formulation of the strategies of the firms. This text join these research, using the Resource-Based Views framework and soft computing, in this case neural networks and fuzzy inference systems, with aims at contributing for the discussion of this subject to overcome its limitations and the new challenges, resulting increasingly complexity and competitive environment, for the strategic management research. The Resource-Based View framework supplies the theoretical underpinnings to use the inimitability degree and immobility degree, resultants of the strategical exploration of the resources of the firms, as constructors to evaluate firm strategic similarity in a competitive environment. Soft computing is a tool to extract subjective data from complexity environments, simulating the ability for learning, perception, evolution and adaptation of human reasoning. The result of this research is the proposal of a model to identify strategic groups, applying the constructors Inimitability Degree and Immobility Degree, and Neuro-fuzzy Inference Systems. To validate the model, a test is performed to the supermarkets industry.
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Ernest, Nicholas D. "UAV Swarm Cooperative Control Based on a Genetic-Fuzzy Approach." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1337954828.

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Porro, Martorell Olga. "A hesitant fuzzy perceptual-based approach to model linguistic assessments." Doctoral thesis, Universitat Politècnica de Catalunya, 2021. http://hdl.handle.net/10803/672127.

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Multiple-criteria or multiple-attribute group decision-making is a sub-field of operations research that seek to find a common and representative solution given the preferences elicited by a pre-defined group, over a set of alternatives and with respect to a set of coherent criteria (or attributes). Recently, the modelling of natural language in these processes has captured the attention of many researchers. Most of the evaluations in a group-decision making context are inherently imprecise, incomplete or vague, and therefore, experts feel more comfortable using their language rather than numerical values. The use of hesitant fuzzy linguistic term sets is one of the recent tools that enables the modelling of linguistic assessments in multiple-criteria decision-making. Nonetheless, advances in hesitant linguistic multi-attribute group decision making require the development of structures flexible enough to deal with unbalanced and multi-granular linguistic information. More tools are needed in order to really grasp the differences in the qualitative reasoning processes of each individual. This thesis, firstly, introduces a perceptual-based distance able to capture differences between unbalanced linguistic assessments, which is based on a lattice structure of hesitant fuzzy linguistic terms. Secondly, this distance is used to define a perceptual-based centroid or central opinion which, in turn, is used to define a consensus measure or degree of agreement within the group. Thirdly, with the aim to deal with multi-perceptual group decision-making contexts, where each decision maker has its own qualitative reasoning approach, a perceptual-based transformation function and a projected algebraic structure are defined. The developed tools can deal with different multi-granularity linguistic environments. Two applications are presented to demonstrate the utility, relevancy and feasibility of the methods. On the one hand, a specific perceptual-based classification and ranking method is introduced and applied to a real group decision making problem in an educational setting. This framework is used to classify and rank a set of secondary students according to their degree of entrepreneurial competency, which is based on real data provided by the Andorra Government. On the other hand, an extended fuzzy multi-perceptual linguistic TOPSIS is designed and applied to a real group decision making problem in the context of smart city governance. This perceptual extension is used to assess the criteria governing the strategic decision making process of energy multinational companies when deciding where to expand its sustainable services and products.
El multiple-criteria o bé multi-attributte group decision-making (MCGDM / MAGDM) és una branca del camp de OR (operations research) l'objectiu del qual és buscar solucions comunes i representatives donades unes preferències d'un grup d'experts definit, sobre un conjunt d'alternatives i en relació a un conjunt coherent de criteris o atributs. L'objectiu d'aquesta tesis és contribuir específicament en l'àrea lingüística de MCGDM / MAGDM millorant les metodologies i marcs matemàtics existents amb l'objectiu de poder modelar qualsevol tipus de situació de presa de decisions en grup que impliqui multi-granularitat i raonament qualitatiu molt heterogeni entre el grup (ús d'etiquetes lingüístiques no balancejades). En concret, la tesis es basa en l'ús de l'eina dels hesitant fuzzy lingüístic term sets (HFLTSs) que fou introduïda per Rodriguez et al (2012) amb l'objectiu de permetre als experts poder donar opinions i preferències lingüístiques usant el seu llenguatge habitual (i no, números) capturant també la incertesa, ambigüitat i manca d'informació característica en aquest tipus de decisions. La majoria d'estructures matemàtiques existents basades en l'ús de HFLTSs en problemes de MCGDM/MAGDM fan la hipòtesis que tots els experts han d'expressar-se usant el mateix set d'etiquetes lingüístiques i/o bé el pes que cada expert dona a cadascuna de les etiquetes ha de ser el mateix. Aquests estructures no són suficientment flexibles per modelar situacions de GDM de multi-granularitat que també incloguin diversitat de raonament qualitatiu amb etiquetes lingüístiques no balancejades de forma simultània. En primer lloc, la present tesis desenvolupa un nou concepte, el perceptual-map, definit sobre l'estructura algebraica de HFLTSs no balancejats i introdueix una nova distància basada en aquesta mètrica. Aquesta distància és utilitzada per definir un centroide (opinió central) i una mesura de consens per a qualsevol situació de MAGDM que necessiti de l'ús d'un set d'etiquetes lingüístiques no balancejat. En segon lloc, una funció de transformació basada en el perceptual-map es defineix per tal de poder modelar simultàniament situacions lingüístiques amb multi-granularitat i poder així, realitzar operacions en un espai projectat. A nivell pràctic, la tesis presenta dos aplicacions reals per demostrar la utilitat i rellevància de les eines matemàtiques desenvolupades. D'una banda, la tesis introdueix un nou mètode de classificació i rànquing, que és aplicat en l'àmbit de l'educació. El nou mètode és utilitzat per classificar i ranquejar els alumnes de secundària de l'escola Andorrana d'acord amb el seu grau de desenvolupament de la competència emprenedora. D'altra banda, s'ha desenvolupat un nou model de TOPSIS anomenat fuzzy multi-perceptual lingüístic TOPSIS, que s'ha aplicat en el context d'avaluació de smart cities. La nova versió de TOPSIS s'ha aplicat amb èxit per avaluar els criteris que governen la decisió estratègica de localització, en el context de ciutats europees, de les multinacionals del sector energètic.
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Umer, Adil. "Sustainability evaluation of transportation infrastructure under uncertainty : a fuzzy-based approach." Thesis, University of British Columbia, 2015. http://hdl.handle.net/2429/53035.

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The construction and maintenance of transportation infrastructure consume significant natural resources, produces considerable waste and uses extensive human capital. Sustainability evaluation of alternative initiatives and policies for developing transportation infrastructure enables decision makers to make informed choices. Despite the availability of numerous sustainability rating tools for roadway infrastructure, there is a need to develop customizable sustainability evaluation tools for informed decision-making. Such tools, unlike the rating systems, ideally need to handle uncertain data, incorporate expert opinion and adapt to project and geographic specific constraints. Deterministic approaches for life cycle cost analysis (LCCA) and life cycle assessment (LCA) have been extensively applied to select sustainable pavement alternatives. However, the information used to conduct LCCA and LCA is often imprecise and vague in early project phases. Therefore, certain technique is required to incorporate and propagate such uncertainties so that the reliability of final results is transparent. Unlike probabilistic methods, fuzzy based techniques are more appropriate to handle uncertainties due to vagueness and imprecision in a computationally efficient manner. This study aimed to investigate the use of fuzzy logic to evaluate sustainability under uncertainty at two levels of infrastructures - Roadways as systems and pavements as components. A novel roadway sustainability evaluation framework was developed using indicators from existing green rating system. A customizable excel-based tool was programmed based on the framework to estimate the sustainability index (SI) of roadways under uncertainty using fuzzy synthetic evaluation (FSE) technique. The FSE technique enables the tool to evaluate reliable and informative SI by incorporating expert opinion. Moreover, fuzzy composite programming (FCP) technique was used to estimate the life cycle environmental and economic sustainability indices (SIs) from LCA and LCCA of pavement alternatives under uncertainty. The FCP technique improved the reliability of final results by propagating input uncertainties to the outputs. Scenario analysis was performed using FSE and FCP techniques to demonstrate the influence of uncertainties and decision maker’s preferences on the overall SI of roadways and pavements respectively. This study demonstrated a compelling utility of fuzzy-based techniques to evaluate sustainability under uncertainty in the early project phases for informed decision-making.
Applied Science, Faculty of
Engineering, School of (Okanagan)
Graduate
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Kishk, Mohammed El-Said. "An integrated fuzzy approach to whole life costing based decision making." Thesis, Robert Gordon University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.369051.

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Wang, Ming-hua. "A knowledge-based system approach for project management decision-making support." Thesis, University of Warwick, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340476.

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Arslan, Dilek. "A Control System Using Behavior Hierarchies And Neuro-fuzzy Approach." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12605743/index.pdf.

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In agent based systems, especially in autonomous mobile robots, modelling the environment and its changes is a source of problems. It is not always possible to effectively model the uncertainity and the dynamic changes in complex, real-world domains. Control systems must be robust to changes and must be able to handle these uncertainties to overcome this problem. In this study, a reactive behaviour based agent control system is modelled and implemented. The control system is tested in a navigation task using an environment, which has randomly placed obstacles and a goal position to simulate an environment similar to an autonomous robot&rsquo
s indoor environment. Then the control system was extended to control an agent in a multi-agent environment. The main motivation of this study is to design a control system which is robust to errors and easy to modify. Behaviour based approach with the advantages of fuzzy reasoning systems is used in the system.
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Книги з теми "FUZZY BASED APPROACH"

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Kolman, Eyal, and Michael Margaliot. Knowledge-Based Neurocomputing: A Fuzzy Logic Approach. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-88077-6.

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Michael, Margaliot, ed. Knowledge-based neurocomputing: A fuzzy logic approach. Berlin: Springer, 2009.

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3

Multistage fuzzy control: A model-based approach to fuzzy control and decision making. Chichester: Wiley, 1997.

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4

Feng, Gang. Analysis and synthesis of fuzzy control systems: A model-based approach. Boca Raton: CRC Presss, 2010.

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5

Analysis and synthesis of fuzzy control systems: A model based approach. Boca Raton: CRC Presss, 2010.

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Controlling accidents and insurers' risks in construction: A fuzzy knowledge-based approach. Hauppauge, NY: Nova Science Publishers, 2009.

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United States. National Aeronautics and Space Administration., ed. Fuzzy sets, rough sets, and modeling evidence: Theory and application : a Dempster-Shafer based approach to compromise decision making with multiattributes applied to product selection. [Clear Lake, Tex.]: Research Institute for Computing and Information Systems, University of Houston-Clear Lake, 1992.

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Korvin, Andre De. Fuzzy sets, rough sets, and modeling evidence: Theory and application : a Dempster-Shafer based approach to compromise decision making with multiattributes applied to product selection. [Clear Lake, Tex.]: Research Institute for Computing and Information Systems, University of Houston-Clear Lake, 1992.

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United States. National Aeronautics and Space Administration., ed. Application of fuzzy logic-neural network based reinforcement learning to proximity and docking operations: Special approach/docking testcase results. [Houston, Tex.]: Research Institute for Computing and Information Systems, University of Houston-Clear Lake, 1993.

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10

Gegov, Alexander. Fuzzy Networks for Complex Systems: A Modular Rule Base Approach. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2010.

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Частини книг з теми "FUZZY BASED APPROACH"

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Lima, Dayvison Chaves, Fabrício Freitas, Gutavo Campos, and Jerffeson Souza. "A Fuzzy Approach to Requirements Prioritization." In Search Based Software Engineering, 64–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23716-4_8.

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Dubois, Didier, Francesc Esteva, Pere Garcia, Lluís Godo, Ramon López De Màntaras, and Henri Prade. "Case-based reasoning: A fuzzy approach." In Fuzzy Logic in Artificial Intelligence, 79–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/bfb0095072.

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Lertworasirikul, Saowanee, Shu-Cherng Fang, Jeffrey A. Joines, and Henry L. W. Nuttle. "Fuzzy Data Envelopment Analysis: A Credibility Approach." In Fuzzy Sets Based Heuristics for Optimization, 141–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-36461-0_10.

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Singh, Alpna, Aruna Tiwari, and Sujata Naegi. "Fuzzy Rough Set Approach Based Classifier." In Swarm, Evolutionary, and Memetic Computing, 550–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-27172-4_65.

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Razali, Razulaimi, and Jafreezal Jaafar. "Fuzzy Based Approach for Complaint Management." In Informatics Engineering and Information Science, 386–400. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25453-6_34.

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de Lourdes Martínez-Villaseñor, María, and Miguel González-Mendoza. "Fuzzy-Based Approach of Concept Alignment." In Ubiquitous Computing and Ambient Intelligence, 172–80. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67585-5_18.

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Kolman, Eyal, and Michael Margaliot. "Knowledge-Based Design of ANNs." In Knowledge-Based Neurocomputing: A Fuzzy Logic Approach, 59–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-88077-6_6.

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Pivoňka, Petr. "Analysis and Design of Fuzzy PID Controller Based on Classical PID Controller Approach." In Fuzzy Control, 186–99. Heidelberg: Physica-Verlag HD, 2000. http://dx.doi.org/10.1007/978-3-7908-1841-3_14.

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Shiu, Simon C. K., X. Z. Wang, and Daniel S. Yeung. "Neuro-Fuzzy Approach for Maintaining Case Bases." In Soft Computing in Case Based Reasoning, 259–73. London: Springer London, 2001. http://dx.doi.org/10.1007/978-1-4471-0687-6_11.

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Castellano, Giovanna, Anna Maria Fanelli, and Maria Alessandra Torsello. "A Fuzzy Set Approach for Shape-Based Image Annotation." In Fuzzy Logic and Applications, 236–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23713-3_30.

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Тези доповідей конференцій з теми "FUZZY BASED APPROACH"

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Hnatkowska, Bogumila, Adrianna Kozierkiewicz, and Marcin Pietranik. "Fuzzy based approach to ontology relations alignment." In 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2021. http://dx.doi.org/10.1109/fuzz45933.2021.9494564.

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Martinez-Jimenez, Pedro Manuel, Jesus Chamorro-Martinez, and Belen Prados-Suarez. "A Fuzzy Approach for Texture-based Segmentation." In 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2020. http://dx.doi.org/10.1109/fuzz48607.2020.9177584.

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Gaeta, Matteo, Francesco Orciuoli, Vincenzo Loia, and Sabrina Senatore. "A fuzzy agent-based approach to trust-based competency management." In 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2011. http://dx.doi.org/10.1109/fuzzy.2011.6007603.

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Baghaei, Kourosh T., and Shahram Rahimi. "Sepsis Prediction: An Attention-Based Interpretable Approach." In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2019. http://dx.doi.org/10.1109/fuzz-ieee.2019.8858808.

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Wang, H., D. Xue, and D. H. Norrie. "A Fuzzy-Based Optimal Delivery Scheduling Approach." In ASME 2000 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/detc2000/cie-14669.

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Abstract A fuzzy-based optimal delivery scheduling approach is introduced in this research. In this approach, optimal delivery scheduling is conducted at three different levels considering (1) one driver and one load, (2) one driver and multiple loads, and, (3) multiple drivers and multiple loads. Fuzzy-based clustering methods are employed to classify delivery tasks into driver groups, load groups, and location groups. The optimal sequence and timing parameters of the delivery tasks are identified using the fuzzy-based clustering results and state-space search. The intelligent optimal delivery scheduling system was implemented using Smalltalk.
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Ashkezari-T, Soheila, and Mohammad-R. Akbarzadeh-T. "Fuzzy-Bayesian network approach to genre-based recommender systems." In 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2010. http://dx.doi.org/10.1109/fuzzy.2010.5584250.

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Boixader, Dionis, and J. Recasens. "Approximating fuzzy preorders and equivalences. A similarity based approach." In 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2010. http://dx.doi.org/10.1109/fuzzy.2010.5584180.

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Purkait, Pulak, and Bhabatosh Chanda. "Fuzzy-rule based approach for single frame super resolution." In 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2013. http://dx.doi.org/10.1109/fuzz-ieee.2013.6622394.

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Naderpour, Mohsen, Jie Lu, and Guangquan Zhang. "A fuzzy dynamic bayesian network-based situation assessment approach." In 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2013. http://dx.doi.org/10.1109/fuzz-ieee.2013.6622430.

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Elomda, Basem Mohamed, Maryam Hazman, Hesham Ahmed Hefny, and Hesham Ahmed Hassan. "MCDM approach based on generalized fuzzy decision map method." In 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2015. http://dx.doi.org/10.1109/fuzz-ieee.2015.7337881.

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Звіти організацій з теми "FUZZY BASED APPROACH"

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Wayland, J. R. Fuzzy logic and a risk-based graded approach for developing S/RIDs: An introduction. Office of Scientific and Technical Information (OSTI), January 1996. http://dx.doi.org/10.2172/172476.

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Eddy, B. G., C. W. Jefferson, and G. F. Bonham-Carter. Mineral potential mapping using a knowledge-based fuzzy logic approach for Melville Island, Northwest Territories. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1994. http://dx.doi.org/10.4095/193496.

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Yoon, Byung. Narrowing the Cognitive Distance Between Engineers and Customers: A Novel Approach, Based on Fuzzy Cognitive Mapping. Portland State University Library, February 2020. http://dx.doi.org/10.15760/etd.7285.

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Borgwardt, Stefan, and Rafael Peñaloza. Undecidability of Fuzzy Description Logics. Technische Universität Dresden, 2011. http://dx.doi.org/10.25368/2022.184.

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Fuzzy description logics (DLs) have been investigated for over two decades, due to their capacity to formalize and reason with imprecise concepts. Very recently, it has been shown that for several fuzzy DLs, reasoning becomes undecidable. Although the proofs of these results differ in the details of each specific logic considered, they are all based on the same basic idea. In this report, we formalize this idea and provide sufficient conditions for proving undecidability of a fuzzy DL. We demonstrate the effectiveness of our approach by strengthening all previously-known undecidability results and providing new ones. In particular, we show that undecidability may arise even if only crisp axioms are considered.
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Tsidylo, Ivan M., Serhiy O. Semerikov, Tetiana I. Gargula, Hanna V. Solonetska, Yaroslav P. Zamora, and Andrey V. Pikilnyak. Simulation of intellectual system for evaluation of multilevel test tasks on the basis of fuzzy logic. CEUR Workshop Proceedings, June 2021. http://dx.doi.org/10.31812/123456789/4370.

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The article describes the stages of modeling an intelligent system for evaluating multilevel test tasks based on fuzzy logic in the MATLAB application package, namely the Fuzzy Logic Toolbox. The analysis of existing approaches to fuzzy assessment of test methods, their advantages and disadvantages is given. The considered methods for assessing students are presented in the general case by two methods: using fuzzy sets and corresponding membership functions; fuzzy estimation method and generalized fuzzy estimation method. In the present work, the Sugeno production model is used as the closest to the natural language. This closeness allows for closer interaction with a subject area expert and build well-understood, easily interpreted inference systems. The structure of a fuzzy system, functions and mechanisms of model building are described. The system is presented in the form of a block diagram of fuzzy logical nodes and consists of four input variables, corresponding to the levels of knowledge assimilation and one initial one. The surface of the response of a fuzzy system reflects the dependence of the final grade on the level of difficulty of the task and the degree of correctness of the task. The structure and functions of the fuzzy system are indicated. The modeled in this way intelligent system for assessing multilevel test tasks based on fuzzy logic makes it possible to take into account the fuzzy characteristics of the test: the level of difficulty of the task, which can be assessed as “easy”, “average", “above average”, “difficult”; the degree of correctness of the task, which can be assessed as “correct”, “partially correct”, “rather correct”, “incorrect”; time allotted for the execution of a test task or test, which can be assessed as “short”, “medium”, “long”, “very long”; the percentage of correctly completed tasks, which can be assessed as “small”, “medium”, “large”, “very large”; the final mark for the test, which can be assessed as “poor”, “satisfactory”, “good”, “excellent”, which are included in the assessment. This approach ensures the maximum consideration of answers to questions of all levels of complexity by formulating a base of inference rules and selection of weighting coefficients when deriving the final estimate. The robustness of the system is achieved by using Gaussian membership functions. The testing of the controller on the test sample brings the functional suitability of the developed model.
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Borgwardt, Stefan. The Complexity of Fuzzy Description Logics over Finite Lattices with Nominals. Technische Universität Dresden, 2014. http://dx.doi.org/10.25368/2022.204.

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The complexity of reasoning in fuzzy description logics (DLs) over finite lattices usually does not exceed that of the underlying classical DLs. This has recently been shown for the logics between L-IALC and L-ISCHI using a combination of automata- and tableau-based techniques. In this report, this approach is modified to deal with nominals and constants in L-ISCHOI. Reasoning w.r.t. general TBoxes is ExpTime-complete, and PSpace-completeness is shown under the restriction to acyclic terminologies in two sublogics. The latter implies two previously unknown complexity results for the classical DLs ALCHO and SO.
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Borgwardt, Stefan, and Rafael Peñaloza. Infinitely Valued Gödel Semantics for Expressive Description Logics. Technische Universität Dresden, 2015. http://dx.doi.org/10.25368/2022.217.

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Fuzzy Description Logics (FDLs) combine classical Description Logics with the semantics of Fuzzy Logics in order to represent and reason with vague knowledge. Most FDLs using truth values from the interval [0; 1] have been shown to be undecidable in the presence of a negation constructor and general concept inclusions. One exception are those FDLs whose semantics is based on the infinitely valued Gödel t-norm (G). We extend previous decidability results for the FDL G-ALC to deal with complex role inclusions, nominals, inverse roles, and qualified number restrictions. Our novel approach is based on a combination of the known crispification technique for finitely valued FDLs and an automata-based procedure for reasoning in G-ALC.
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Karam, Sofia, Morteza Nagahi, Vidanelage Dayarathna, Junfeng Ma, Raed Jaradat, and Michael Hamilton. Integrating systems thinking skills with multi-criteria decision-making technology to recruit employee candidates. Engineer Research and Development Center (U.S.), June 2021. http://dx.doi.org/10.21079/11681/41026.

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The emergence of modern complex systems is often exacerbated by a proliferation of information and complication of technologies. Because current complex systems challenges can limit an organization's ability to efficiently handle socio-technical systems, it is essential to provide methods and techniques that count on individuals' systems skills. When selecting future employees, companies must constantly refresh their recruitment methods in order to find capable candidates with the required level of systemic skills who are better fit for their organization's requirements and objectives. The purpose of this study is to use systems thinking skills as a supplemental selection tool when recruiting prospective employees. To the best of our knowledge, there is no prior research that studied the use of systems thinking skills for recruiting purposes. The proposed framework offers an established tool to HRM professionals for assessing and screening of prospective employees of an organization based on their level of systems thinking skills while controlling uncertainties of complex decision-making environment with the fuzzy linguistic approach. This framework works as an expert system to find the most appropriate candidate for the organization to enhance the human capital for the organization.
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