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    고객 만족 서비스를 위한 퍼지 추론 시스템 구조

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    https://www.riss.kr/link?id=A101700970

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    Recently most parking control systems provide customers with various services, but most of the services are just the extension of parking spaces, automatic parking control system and so on. It is essential to use the satisfaction degree as the extent that customer are satisfied with parking control system to improve the quality of the system services and diversify the system services. The degree of satisfaction is different from customer to customer in same condition and can be represented as linguistic variables. In this paper, we present therefore a technique that quantify how much customer are satisfied with parking control system and fuzzy inference system architecture as a solution that can help us to make a efficient decision for these parking problems. In this architecture, inference engine using fuzzy logic compares context data with the rules in the fuzzy rule-based system, gets the sub-results, aggregates them and defuzzifies the aggregated result using MATLAB application programming to obtain crisp value. Fuzzy inference system architecture presented in this paper, can be used as a efficient method to analyze the satisfaction degree which is represented as fuzzy linguistic variables by human emotion. And it can be used to improve the satisfaction degree of not only parking system but also other service systems of various domains.
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    Recently most parking control systems provide customers with various services, but most of the services are just the extension of parking spaces, automatic parking control system and so on. It is essential to use the satisfaction degree as the extent ...

    Recently most parking control systems provide customers with various services, but most of the services are just the extension of parking spaces, automatic parking control system and so on. It is essential to use the satisfaction degree as the extent that customer are satisfied with parking control system to improve the quality of the system services and diversify the system services. The degree of satisfaction is different from customer to customer in same condition and can be represented as linguistic variables. In this paper, we present therefore a technique that quantify how much customer are satisfied with parking control system and fuzzy inference system architecture as a solution that can help us to make a efficient decision for these parking problems. In this architecture, inference engine using fuzzy logic compares context data with the rules in the fuzzy rule-based system, gets the sub-results, aggregates them and defuzzifies the aggregated result using MATLAB application programming to obtain crisp value. Fuzzy inference system architecture presented in this paper, can be used as a efficient method to analyze the satisfaction degree which is represented as fuzzy linguistic variables by human emotion. And it can be used to improve the satisfaction degree of not only parking system but also other service systems of various domains.

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    참고문헌 (Reference)

    1 이광형, "퍼지이론 및 응용" 홍릉과학 출판사 1991

    2 유정상, "주차 관리시스템에서 지능형 추론 구조" 한국경영공학회 13 (13): 231-237, 2008

    3 도용태, "인공지능 개념 및 응용" 사이텍 미디어사 2001

    4 권희철, "고객 만족도를 고려한 주차관리시스템에서 혼합 추론 구조" 한국경영공학회 14 (14): 169-177, 2009

    5 "The MathWorks"

    6 Dan W.Patterson, "Introduction to Artificial Intelligence and Expert Systems" Prentice-Hall 1990

    7 Dan W.Patterson, "Introduction to Artificial Intelligence and Expert Systems" Prentice-Hall 1990

    8 Ivan G, "Intelligent Car Parking Locator Service" 2 (2): 2008

    9 Roman M, "Gaia:A Middleware Infrastructure to Enable Active Spaces" 10 (10): 74-83, 2002

    10 S.Yasunobu, "Fuzzy Target Acquired by Reinforcement Learning for Parking Control" 1303-1308, 2003

    1 이광형, "퍼지이론 및 응용" 홍릉과학 출판사 1991

    2 유정상, "주차 관리시스템에서 지능형 추론 구조" 한국경영공학회 13 (13): 231-237, 2008

    3 도용태, "인공지능 개념 및 응용" 사이텍 미디어사 2001

    4 권희철, "고객 만족도를 고려한 주차관리시스템에서 혼합 추론 구조" 한국경영공학회 14 (14): 169-177, 2009

    5 "The MathWorks"

    6 Dan W.Patterson, "Introduction to Artificial Intelligence and Expert Systems" Prentice-Hall 1990

    7 Dan W.Patterson, "Introduction to Artificial Intelligence and Expert Systems" Prentice-Hall 1990

    8 Ivan G, "Intelligent Car Parking Locator Service" 2 (2): 2008

    9 Roman M, "Gaia:A Middleware Infrastructure to Enable Active Spaces" 10 (10): 74-83, 2002

    10 S.Yasunobu, "Fuzzy Target Acquired by Reinforcement Learning for Parking Control" 1303-1308, 2003

    11 R.A.Ribeiro, "Fuzzy Space Monitoring and Fault Detection Applications" 15 (15): 267-286, 2006

    12 George J.Klir, "Fuzzy Sets,Fuzzy Logic,and Fuzzy Systems" World Scientific 1996

    13 H.-J.Zimmermann, "Fuzzy Set Theory-and Its Applications" Kluwer-Nijhoff Publishing 1985

    14 Z.Q. Liu, "Fuzzy Neural Network in Case-Based Diagnostic System" 5 (5): 209-222, 1997

    15 M.B.Celik,, "Fault detection in internal combustion engines using fuzzy logic" 221 : 579-587, 2007

    16 Shobhit S., "An intelligent Architecture for Metropolitan Area Parking Control and Toll Collection" 723-728, 2005

    17 Gu T, "A middleware for building context-aware mobile services" 2656-2660, 2004

    18 C.-C.Huang,, "A Bayesian hierarchical detection framework for parking space detection" 2097-2100, 2008

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    학술지 이력

    학술지 이력
    연월일 이력구분 이력상세 등재구분
    2026 평가 재인증평가 신청대상 (재인증)
    2020-01-01 등재 등재학술지 유지 (재인증) KCI등재
    2017-01-01 등재 등재학술지 유지 (계속평가) KCI등재
    2013-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2010-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2007-01-01 등재 등재학술지 선정 (등재후보2차) KCI등재
    2006-01-01 등재 등재후보 1차 PASS (등재후보1차) KCI등재후보
    2004-07-01 등재 등재후보학술지 선정 (신규평가) KCI등재후보
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    학술지 인용정보

    학술지 인용정보
    기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
    2016 0.44 0.44 0.44
    KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
    0.43 0.38 0.58 0.15
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