• Title/Summary/Keyword: fuzzy theory

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ROUGH SET THEORY APPLIED TO INTUITIONISTIC FUZZY IDEALS IN RINGS

  • Jun, Young-Bae;Park, Chul-Hwan;Song, Seok-Zun
    • Journal of applied mathematics & informatics
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    • v.25 no.1_2
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    • pp.551-562
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    • 2007
  • This paper concerns a relationship between rough sets, intuitionistic fuzzy sets and ring theory. We consider a ring as a universal set and we assume that the knowledge about objects is restricted by an intuitionistic fuzzy ideal. We apply the notion of intutionistic fuzzy ideal of a ring for definitions of the lower and upper approximations in a ring. Some properties of the lower and upper approximations are investigated.

Decomposition of fuzzy ideal continuity via fuzzy idealization

  • Zahran, Ahmed M.;El-Baki, S. Ahmed Abd;Saber, Yaser Mohammed
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.9 no.2
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    • pp.83-93
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    • 2009
  • Recently, El-Naschie has shown that the notion of fuzzy topology may be relevant to quantum paretical physics in connection with string theory and E-infinity space time theory. In this paper, we study the concepts of r-fuzzy semi-I-open, r-fuzzy pre-I-open, r-fuzzy $\alpha$-I-open and r-fuzzy $\beta$-I-open sets, which is properly placed between r-fuzzy openness and r-fuzzy $\alpha$-I-openness (r-fuzzy pre-I-openness) sets regardless the fuzzy ideal topological space in Sostak sense. Moreover, we give a decomposition of fuzzy continuity, fuzzy ideal continuity and fuzzy ideal $\alpha$-continuity, and obtain several characterization and some properties of these functions. Also, we investigate their relationship with other types of function.

A study of hesitant fuzzy soft multiset theory

  • Onyeozili, I.A.;Balami, Holyheavy;Peter, C.M.
    • Annals of Fuzzy Mathematics and Informatics
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    • v.16 no.3
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    • pp.261-284
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    • 2018
  • In this paper, we recall the definition of soft set, fuzzy soft set, hesitant fuzzy set and hesitant fuzzy soft set and some of their examples. We define the concept of hesitant fuzzy soft multiset which combines hesitant fuzzy soft set and soft multiset theory. We also define basic terms in hesitant fuzzy soft multiset with relevant examples. Some basic operations such as restricted intersection, extended intersection, union, restricted union, AND-product and OR-product and their properties are given, supported with illustrative examples. We finally establish some important results, including De Morgan's inclusions and laws.

Application of the Fuzzy Set Theory to Analysis of Accident Progression Event Trees with Phenomenological Uncertainty Issues (현상학적 불확실성 인자를 가진 사고진행사건수목의 분석을 위한 퍼지 집합이론의 응용)

  • Ahn, Kwang-Il;Chun, Moon-Hyun
    • Nuclear Engineering and Technology
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    • v.23 no.3
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    • pp.285-298
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    • 1991
  • An example application of the fuzzy set theory is first made to a simple portion of a given accident progression event tree with typical qualitative fuzzy input data, and thereby computational algorithms suitable for application of the fuzzy set theory to the accident progression event tree analysis are identified and illustrated with example applications. Then the procedure used in the simple example is extended to extremely complex accident progression event trees with a number of phenomenological uncertainty issues, i.e., a typical plant damage state‘SEC’of the Zion Nuclear Power Plant risk assessment. The results show that the fuzzy averages of the fuzzy outcomes are very close to the mean values obtained by current methods. The main purpose of this paper is to provide a formal procedure for application of the fuzzy set theory to accident progression event trees with imprecise and qualitative branch probabilities and/or with a number of phenomenological uncertainty issues.

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A study on a design of developed-ERES/WCS using the ASR and fuzzy set theory as a part of human interface technique (Human interface 기술의 일환으로서 ASR과 fuzzy set theory를 이용한 developed-ERES/WCS 설계에 관한 연구)

  • 이순요;이창민;박세권
    • 제어로봇시스템학회:학술대회논문집
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    • 1988.10a
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    • pp.76-81
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    • 1988
  • As a means of human interface, this study designs Developed-ERES/WCS with voice recognition capability and fuzzy set theory. In the advanced teleoperator system, when an error occurs on the automatic mode, the error is recovered after the automatic mode is changed into the manual mode intervened by a human. The purpose of this study is to reduce human work load and to shorten error recovery time during error recovery.

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Optimal Operation Scheduling Using Possibility Fuzzy Theory on Cogeneration Systems Connected with Auxiliary Equipment (각종 보조설비가 연계된 열병합발전시스템에서 가능성 퍼지이론을 적용한 최적운전계획수립)

  • Kim, Sung-Il;Jung, Chang-Ho;Lee, Jong-Beon
    • Proceedings of the KIEE Conference
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    • 1995.11a
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    • pp.128-130
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    • 1995
  • This paper presents the optimal operation scheduling on cogeneration systems connected with auxiliary equipment by using the possibility fuzzy theory. The probability fuzzy theory is a method to obtain the possibility of the solution from the fuzzification of coefficients. Simulation is carried out to obtain the boundary of heat production in each time interval. Simulation results shows effectively the flexible operation boundary to establish operation scheduling.

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Determination of the Input/Output Relations and Rule Generation for Fuzzy Combustion Control System of Refuse Incinerator using Rough Set Theory (Rough Set 이론을 이용한 쓰레기 소각로의 퍼지제어 시스템을 위한 입출력 관계 설정 및 규칙 생성)

  • 방원철;변증남
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1997.11a
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    • pp.81-86
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    • 1997
  • It is proposed, for fuzzy combustion control system of refuse incinerator to find the relationship between inputs and outputs and to generate rules to control by using rough set theory. It is not easy to find out the corresponding inputs for each output and the control rules with incomplete or imprecise information consisting expert knowledge, process and manipulator values in the field, and operation manual for the given system. Most decision problems can be formulated employing decision table formalism. A decision table on fuzzy combustion control system for refuse incinerator is simplified and produces control(rules). The I/O realtions and the control rules found by rough set theory are compared with the previous result.

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Forecasting Project Cost and Time using Fuzzy Set Theory and Contractors' Judgment

  • Alshibani, Adel
    • International conference on construction engineering and project management
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    • 2015.10a
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    • pp.174-178
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    • 2015
  • This paper presents a new method for forecasting construction project cost and time at completion or at any intermediate time horizon of the project duration. The method is designed to overcome identified limitations of current applications of earned value method in forecasting project cost and time. The proposed method usesfuzzy set theory to model uncertainties associated with project performance and it integrates the earned value technique and the contractors' judgement. The fuzzy set theory is applied as an alternative approach to deterministic and probabilistic methods. Using fuzzy set theory allows contractors to: (1) perform risk analysis for different scenarios of project performance indices, and (2) perform different scenarios expressing vagueness and imprecision of forecasted project cost and time using a set of measures and indices. Unlike the current applications of Earned Value Method(EVM), The proposed method has a numberof interesting features: (1) integrating contractors' judgement in forecasting project performance; (2) enabling contractors to evaluate the risk associated with cost overrun in much simpler method comparing with that of simulation, and (3) accounting for uncertainties involved in the forecasting project cost.

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Adaptive Clustering Algorithm for Recycling Cell Formation: An Application of Fuzzy ART Neural Networks

  • Seo, Kwang-Kyu;Park, Ji-Hyung
    • Journal of Mechanical Science and Technology
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    • v.18 no.12
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    • pp.2137-2147
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    • 2004
  • The recycling cell formation problem means that disposal products are classified into recycling part families using group technology in their end-of-life phase. Disposal products have the uncertainties of product status by usage influences during product use phase, and recycling cells are formed design, process and usage attributes. In order to deal with the uncertainties, fuzzy set theory and fuzzy logic-based neural network model are applied to recycling cell formation problem for disposal products. Fuzzy C-mean algorithm and a heuristic approach based on fuzzy ART neural network is suggested. Especially, the modified Fuzzy ART neural network is shown that it has a good clustering results and gives an extension for systematically generating alternative solutions in the recycling cell formation problem. Disposal refrigerators are shown as examples.