• Title/Summary/Keyword: set theory

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Generalized Intuitionistic Fuzzy Soft Sets

  • Park, Jin-Han;Kwun, Young-Chel;Hwang, Jin-Soo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.3
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    • pp.389-394
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    • 2011
  • The notion of generalized intuitionistic fuzzy soft set theory is proposed. Our generalized intuitionistic fuzzy soft set theory is a combination of the generalized intuitionistic fuzzy set theory and the soft set theory. In other words, our generalized intuitionistic fuzzy soft set theory is an extension of the intuitionistic fuzzy soft set theory. The complement, "and" and "or" operations are defined on the generalized intuitionistic fuzzy soft sets. Their basic properties for the generalized intuitionistic fuzzy soft sets are also presented and discussed.

A Philosophical Implication of Rough Set Theory (러프집합론의 철학적 함의)

  • Park, Chang Kyun
    • Korean Journal of Logic
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    • v.17 no.2
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    • pp.349-358
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    • 2014
  • Human being has attempted to solve the problem of imperfect knowledge for a long time. In 1982 Pawlak proposed the rough set theory to manipulate the problem in the area of artificial intelligence. The rough set theory has two interesting properties: one is that a rough set is considered as distinct sets according to distinct knowledge bases, and the other is that distinct rough sets are considered as one same set in a certain knowledge base. This leads to a significant philosophical interpretation: a concept (or an event) may be understood as different ones from different perspectives, while different concepts (or events) may be understood as a same one in a certain perspective. This paper claims that such properties of rough set theory produce a mathematical model to support critical realism and theory ladenness of observation in the philosophy of science.

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Fuzzy Sets and Decision Marking in Nuclear Science

  • Ruan, D.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1058-1061
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    • 1993
  • Fuzzy set theory has been extensively researched in various fields of engineering. In nuclear science, a significant influence of fuzzy sets can be noticed. However, applications of fuzzy set theory to nuclear engineering is novel. In this paper, we start with a basic statement of the decision-making process based on fuzzy set theory, and then apply it to nuclear science with some practical applications (a fuzzy decision making in an accidental release to the atmosphere as well as in a problem of land suitability classification). We believe that the use of fuzzy set theory in nuclear science has potential advantages.

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Proposals on Teaching the Set Theory in Secondary School (집합교육의 개선에 대한 몇 가지 제언)

  • 이만근
    • Journal of Educational Research in Mathematics
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    • v.11 no.1
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    • pp.103-111
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    • 2001
  • The set concept has long been recognized as important for organizing traditional mathematics. Although 'to understand mathematical structure' is an important educational purpose, we think that leaching the abstract set theory in the 7th grade is too early. In this paper, we reviewed the set theory in the secondary school and we made some proposals such like that we must accept the term 'set' as 'collection' in 7th grade.

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A NOTE ON WEAK EXCLUDED MIDDLE LAW

  • Chanyoung Sung
    • Journal of the Chungcheong Mathematical Society
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    • v.36 no.1
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    • pp.9-11
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    • 2023
  • Intuitionistic Zermelo-Fraenkel (IZF) set theory is a set theory without the axiom of choice and the law of excluded middle (LEM). The weak excluded middle law (WEM) states that ¬𝜑∨¬¬𝜑 for any formula 𝜑. In IZF we show that LEM is equivalent to WEM plus the condition that any set not equal to the empty set has an element.

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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Inductive Learning Algorithm using Rough Set Theory (Rough Set 이론을 이용한 연역학습 알고리즘)

  • 방원철;변증남
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1997.10a
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    • pp.331-337
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    • 1997
  • In this paper we will discuss a type of inductive learning called learning from examples, whose task is to induce general descriptions of concepts from specific instances of these concepts. In many real life situations however new instances can be added to the set of instances. It is first proposed within the framework of rough set theory, for such cases, an algorithm to find minimal set of rules for decision tables without recalculation for overall set of instances. The method of learning presented here is based on a rough set concept proposed by Pawlak[2]. It is shown an algorithm to fund minimal set of rules using reduct change theorems giving criteria for minimum recalculation and an illustrative example.

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A Hybrid Credit Rating System using Rough Set Theory (러프집합을 이용한 통합형 채권등급 평가모형 구축에 관한 연구)

  • 박기남;이훈영;박상국
    • Journal of the Korean Operations Research and Management Science Society
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    • v.25 no.3
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    • pp.125-135
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    • 2000
  • Many different statistical and artificial intelligent techniques have been applied to improve the predictability of credit rating. Hybrid models and systems have also been developed by effectively combining different modeling processes or combining the outcomes of individual models. In this paper, we introduced the rough set theory and developed a hybrid credit rating system that combines individual outcomes in terms of rough set theory. An experiment was conducted to compare the prediction capability of the system with those of other methods. The proposed system based on rough set method outperformed the others.

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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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Integration rough set theory and case-base reasoning for the corporate credit evaluation (러프집합이론과 사례기반추론을 결합한 기업신용평가 모형)

  • Roh, Tae-Hyup;Yoo Myung-Hwan;Han In-Goo
    • The Journal of Information Systems
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    • v.14 no.1
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    • pp.41-65
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    • 2005
  • The credit ration is a significant area of financial management which is of major interest to practitioners, financial and credit analysts. The components of credit rating are identified decision models are developed to assess credit rating an the corresponding creditworthiness of firms an accurately ad possble. Although many early studies demonstrate a priori which of these techniques will be most effective to solve a specific classification problem. Recently, a number of studies have demonstrate that a hybrid model integration artificial intelligence approaches with other feature selection algorthms can be alternative methodologies for business classification problems. In this article, we propose a hybrid approach using rough set theory as an alternative methodology to select appropriate attributes for case-based reasoning. This model uses rough specific interest lies in lthe stable combining of both rough set theory to extract knowledge that can guide dffective retrevals of useful cases. Our specific interest lies in the stable combining of both rough set theory and case-based reasoning in the problem of corporate credit rating. In addition, we summarize backgrounds of applying integrated model in the field of corporate credit rating with a brief description of various credit rating methodologies.

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