• Title/Summary/Keyword: 퍼지 추론시스템

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Flood Estimation Using Neuro-Fuzzy Technique (Neuro-Fuzzy 기법을 이용한 홍수예측)

  • Ji, Jung-Won;Choi, Chang-Won;Yi, Jae-Eung
    • Proceedings of the Korea Water Resources Association Conference
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    • 2012.05a
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    • pp.128-132
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    • 2012
  • 물은 생물의 생존을 위해 필수적인 요소로 인류가 시작된 이래로 물을 효율적으로 이용하고 안전하게 관리하기 위한 노력은 계속되어 왔다. 최근 지구 온난화가 주요 원인으로 알려진 국지성 집중호우의 피해는 매우 심각하며, 이로 인해 치수에 대한 중요성은 날로 커지고 있다. 지금까지 사용해 왔던 홍수 예 경보 과정은 특정 지점의 유출량을 예측하기 위해서 강우-유출 모형을 운영하였다. 그러나 물리적 모형의 경우 운영에 필요한 매개변수의 결정과정이 복잡하고, 매개변수 결정을 위해 많은 자료를 필요로 한다. 또한 그 매개변수의 결정과정은 많은 불확실성을 포함하고 있어서 모형의 운영을 위한 전처리과정과 계산과정을 거치는 동안 발생한 오차가 누적되어 결과물 속에는 많은 오차가 포함되어 있다. 본 연구에서는 기존의 홍수 예 경보 시스템의 문제점과 불확실성을 최대한 감소시키고 더 우수한 유출량 예측을 위해 neuro-fuzzy 추론 기법을 이용한 모형인 ANFIS(Adaptive Neuro-Fuzzy Inference System)를 사용하여 하천수위를 예측하였다. ANFIS는 신경회로망과 퍼지이론을 결합한 기법으로 신경회로망의 구조와 학습 능력을 이용하여 제어환경에서 획득한 입 출력 정보로부터 언어변수의 membership 함수와 제어규칙을 제어 대상에 적합하도록 자동으로 조종하는 기법이다. 본 연구에서는 ANFIS를 사용하여 탄천 하류에 위치한 대곡교의 수위를 예측하였다. 분석을 위해 2007년부터 2011년까지의 탄천 유역의 관측 강우자료와 수위 자료 중 강우강도와 지속시간, 강우 형태에 따라 7개의 강우사상을 선정하였다. 학습자료 및 보정자료의 변화에 따른 예측 오차를 비교하여 모형의 적용성과 적정성을 평가하였다. 적용결과 입력자료 구성의 경우 해당 시간의 강우량 및 수위자료와 10분 전 강우자료를 이용한 모델이 가장 우수한 예측을 보였고, 학습자료의 경우 자료의 길이가 길고, 최대홍수량이 큰 경우 가장 우수한 예측 결과를 보였다. 본 연구의 적용결과 가장 우수한 모형의 경우 30분 예측 첨두수위 오차는 0.32%, RMSE는 0.05m 이고 예측시간이 길어짐에 따라 오차가 비선형적으로 증가하는 경향을 보였다.

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Accuracy Improvement of Laser Navigation System using FIS and Reliability (FIS와 신뢰도를 이용한 레이저 내비게이션의 정밀도 향상)

  • Jung, Eun-Kook;Kim, Jung-Min;Jung, Kyung-Hoon;Kim, Sung-Shin
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.3
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    • pp.383-388
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    • 2011
  • This paper presents to study the accuracy improvement of the laser navigation using FIS(fuzzy inference system) and the reliability. As wireless guidance system, the top-mounted laser with the laser navigation can rotate $360^{\circ}$ with phototransistor or other optical sensors that read the return signal from reflectors mounted at the perimeter of the workspace. The type of major existing guidance systems is a wire guidance system. Because they have high accuracy and fast response time, they are used to most industries. However, their installation cost is very expensive and maintenance is very difficult because their sensors are placed approximately 1 inch below the ground or embedded in the floor. To solve those problems, the laser navigation was developed as a wire guidance system. It does not need to reconstruct a floor or ground. And it can reduce costs of installation and maintenance because changing the layout is easy. However, it is difficult to apply to an industrial field because it is easily affected by disturbances which cause loss and damage of data, and has slow respond time. Therefore, we study the accuracy improvement of the laser navigation. The proposed method is a correction method using reliability of the laser navigation. here, reliability is calculated by FIS which is designed with the analyzed characteristics of the laser navigation. For performance comparison, we use original position data form the laser navigation and position data corrected by original reliability from the laser navigation. In experimental result, we verified that the performance of the proposed method compared the others is improved by about 50% or more.

Automatic Recommendation of (IP)TV programs based on A Rank Model using Collaborative Filtering (협업 필터링을 이용한 순위 정렬 모델 기반 (IP)TV 프로그램 자동 추천)

  • Kim, Eun-Hui;Pyo, Shin-Jee;Kim, Mun-Churl
    • Journal of Broadcast Engineering
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    • v.14 no.2
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    • pp.238-252
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    • 2009
  • Due to the rapid increase of available contents via the convergence of broadcasting and internet, the efficient access to personally preferred contents has become an important issue. In this paper, for recommendation scheme for TV programs using a collaborative filtering technique is studied. For recommendation of user preferred TV programs, our proposed recommendation scheme consists of offline and online computation. About offline computation, we propose reasoning implicitly each user's preference in TV programs in terms of program contents, genres and channels, and propose clustering users based on each user's preferences in terms of genres and channels by dynamic fuzzy clustering method. After an active user logs in, to recommend TV programs to the user with high accuracy, the online computation includes pulling similar users to an active user by similarity measure based on the standard preference list of active user and filtering-out of the watched TV programs of the similar users, which do not exist in EPG and ranking of the remaining TV programs by proposed rank model. Especially, in this paper, the BM (Best Match) algorithm is extended to make the recommended TV programs be ranked by taking into account user's preferences. The experimental results show that the proposed scheme with the extended BM model yields 62.1% of prediction accuracy in top five recommendations for the TV watching history of 2,441 people.

An Implementation of Lighting Control System using Interpretation of Context Conflict based on Priority (우선순위 기반의 상황충돌 해석 조명제어시스템 구현)

  • Seo, Won-Il;Kwon, Sook-Youn;Lim, Jae-Hyun
    • Journal of Internet Computing and Services
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    • v.17 no.1
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    • pp.23-33
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    • 2016
  • The current smart lighting is shaped to offer the lighting environment suitable for current context, after identifying user's action and location through a sensor. The sensor-based context awareness technology just considers a single user, and the studies to interpret many users' various context occurrences and conflicts lack. In existing studies, a fuzzy theory and algorithm including ReBa have been used as the methodology to solve context conflict. The fuzzy theory and algorithm including ReBa just avoid an opportunity of context conflict that may occur by providing services by each area, after the spaces where users are located are classified into many areas. Therefore, they actually cannot be regarded as customized service type that can offer personal preference-based context conflict. This paper proposes a priority-based LED lighting control system interpreting multiple context conflicts, which decides services, based on the granted priority according to context type, when service conflict is faced with, due to simultaneous occurrence of various contexts to many users. This study classifies the residential environment into such five areas as living room, 'bed room, study room, kitchen and bath room, and the contexts that may occur within each area are defined as 20 contexts such as exercising, doing makeup, reading, dining and entering, targeting several users. The proposed system defines various contexts of users using an ontology-based model and gives service of user oriented lighting environment through rule based on standard and context reasoning engine. To solve the issue of various context conflicts among users in the same space and at the same time point, the context in which user concentration is required is set in the highest priority. Also, visual comfort is offered as the best alternative priority in the case of the same priority. In this manner, they are utilized as the criteria for service selection upon conflict occurrence.