• 제목/요약/키워드: Organizing

검색결과 1,987건 처리시간 0.026초

룩업 테이블을 이용한 자동 학습 퍼지 제어기의 설계에 관한 연구 (Design of a Self-Organizing Fuzzy Controller Using the Look-Up Tables)

  • 이용노;김태원;서일홍
    • 전자공학회논문지B
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    • 제29B권9호
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    • pp.76-87
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    • 1992
  • A novel self-organizing fuzzy plus PD control algorithm is proposed, where the proposed controller consists of a typical fuzzy reasoning part and self organizing part in which both on-line and off-line algorithms are employed to modify the Look-Up Table(LUT) for the fuzzy control rules and to decide how much fuzzy rules are to be modifid after evaluating the control performance, respectively. And the fuzzy controller is replaced by a PD controller in a prespecified region nearby the set point for good settling actions, where gain parameters are determined by fuzzy rules based on the magnitude of error velocity at the instant when the output penetrates into the prespecified region. To show the effectiveness of the proposed controller, extensive computer simulation results as well as experimental results are illustrated for an inverted pendulum system.

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Improvement of Self Organizing Maps using Gap Statistic and Probability Distribution

  • Jun, Sung-Hae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제8권2호
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    • pp.116-120
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    • 2008
  • Clustering is a method for unsupervised learning. General clustering tools have been depended on statistical methods and machine learning algorithms. One of the popular clustering algorithms based on machine learning is the self organizing map(SOM). SOM is a neural networks model for clustering. SOM and extended SOM have been used in diverse classification and clustering fields such as data mining. But, SOM has had a problem determining optimal number of clusters. In this paper, we propose an improvement of SOM using gap statistic and probability distribution. The gap statistic was introduced to estimate the number of clusters in a dataset. We use gap statistic for settling the problem of SOM. Also, in our research, weights of feature nodes are updated by probability distribution. After complete updating according to prior and posterior distributions, the weights of SOM have probability distributions for optima clustering. To verify improved performance of our work, we make experiments compared with other learning algorithms using simulation data sets.

Advanced Self-organizing Neural Networks with Fuzzy Polynomial Neurons : Analysis and Design

  • Oh, Sung-Kwun;Lee , Dong-Yoon
    • KIEE International Transaction on Systems and Control
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    • 제12D권1호
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    • pp.12-17
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    • 2002
  • We propose a new category of neurofuzzy networks- Self-organizing Neural Networks(SONN) with fuzzy polynomial neurons(FPNs) and discuss a comprehensive design methodology supporting their development. Two kinds of SONN architectures, namely a basic SONN and a modified SONN architecture are dicussed. Each of them comes with two types such as the generic and the advanced type. SONN dwells on the ideas of fuzzy rule-based computing and neural networks. Simulation involves a series of synthetic as well as experimental data used across various neurofuzzy systems. A comparative analysis is included as well.

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민간신앙(民間信仰)을 중심(中心)으로 한 지리산(智異山) 화엄사(華嚴寺) 가람(伽藍)의 조영사상(造營思想)에 관한 연구(硏究) (A study on the Organizing Principle of Hwaeomsa Temple in Ghiri Mountain Focused on the Folk Beliefs)

  • 이동영;최효승
    • 한국농촌건축학회논문집
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    • 제2권3호
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    • pp.85-97
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    • 2000
  • In the organizing principle of Hwaeomsa temple, we could see the procedure of absorption and combination on folk beliefs and Buddhism like other temples. One of Representative folk beliefs took in and combined in its temple is Sam-Sung-Gak, which is located at the same place with Won-Tong-Geon. And Myong-Bu-Geon is affected by the Ten-Kings belief of Taoism very deeply, is also very rare folk belief case grown naturally. The diversification of Buddhist sanctum' function is absorption and combination between proper belief for the Buddhist Goddess of Mercy and folk native beliefs.

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Detecting cell cycle-regulated genes using Self-Organizing Maps with statistical Phase Synchronization (SOMPS) algorithm

  • 김창식;차홍준;배철수;김문환
    • 한국정보전자통신기술학회논문지
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    • 제1권2호
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    • pp.39-50
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    • 2008
  • Developing computational methods for identifying cell cycle-regulated genes has been one of important topics in systems biology. Most of previous methods consider the periodic characteristics of expression signals to identify the cell cycle-regulated genes. However, we assume that cell cycle-regulated genes are relatively active having relatively many interactions with each other based on the underlying cellular network. Thus, we are motivated to apply the theory of multivariate phase synchronization to the cell cycle expression analysis. In this study, we apply the method known as "Self-Organizing Maps with statistical Phase Synchronization (SOMPS)", which is the combination of self-organizing map and multivariate phase synchronization, producing several subsets of genes that are expected to have interactions with each other in their subset (Kim, 2008). Our evaluation experiments show that the SOMPS algorithm is able to detect cell cycle-regulated genes as much as one of recently reported method that performs better than most existing methods.

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자기조직화 신경망과 계층적 군집화 기법(SONN-HC)을 이용한 인터넷 뱅킹의 고객세분화 모형구축 (Customer Segmentation Model for Internet Banking using Self-organizing Neural Networks and Hierarchical Gustering Method)

  • 신택수;홍태호
    • Asia pacific journal of information systems
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    • 제16권3호
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    • pp.49-65
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    • 2006
  • This study proposes a model for customer segmentation using the psychological characteristics of Internet banking customers. The model was developed through two phased clustering method, called SONN-HC by integrating self-organizing neural networks (SONN) and hierarchical clustering (HC) method. We applied the SONN-HC method to internet banking customer segmentation and performed an empirical analysis with 845 cases. The results of our empirical analysis show the psychological characteristics of Internet banking customers have significant differences among four clusters of the customers created by SONN-HC. From these results, we found that the psychological characteristics of Internet banking customers had an important role of planning a strategy for customer segmentation in a financial institution.

Korean Guidelines for Diagnosis and Management of Interstitial Lung Diseases: Part 4. Cryptogenic Organizing Pneumonia

  • Choi, Sue In;Jung, Won Jai;Lee, Eun Joo
    • Tuberculosis and Respiratory Diseases
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    • 제84권3호
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    • pp.171-175
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    • 2021
  • Cryptogenic organizing pneumonia (COP) is a type of idiopathic interstitial pneumonia with an acute or subacute clinical course. Bilateral lung consolidations located in the subpleural area and bronchovascular bundle are the most common findings on chest high-resolution computed tomography. The pathologic manifestations include granulation tissue in the alveoli, alveolar ducts, and bronchioles. COP responds fairly well to glucocorticoid monotherapy with rapid clinical improvement, but recurrence is common. However, treatment with combined immunosuppressant agents is not recommended, even if the COP patient does not respond to glucocorticoid monotherapy with expert opinion.

SDN 환경에서 자기조직화지도 신경망을 이용한 분산 컨트롤러 (Distributed controllers using a Self-Organizing Map Neural Network in SDN environment)

  • 유승언;김민우;이병준;김경태;윤희용
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2019년도 제59차 동계학술대회논문집 27권1호
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    • pp.47-48
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    • 2019
  • 본 논문에서는 신경망의 일종인 자기조직화지도(Self Organizing Map)을 이용하여 컨트롤러의 순서를 정하는 모델을 제안하였다. 자기조직화지도는 자율 학습에 의한 클러스터링을 수행하는 알고리즘으로써 컨트롤러에 가중치를 부여하고 컨트롤러 간 거리를 계산하여 효율적인 컨트롤러 선택을 목표로 한다.

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지능형 Self-Organizing Network를 위한 설명 가능한 기계학습 연구 동향 (Trend in eXplainable Machine Learning for Intelligent Self-organizing Networks)

  • 권동승;나지현
    • 전자통신동향분석
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    • 제38권6호
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    • pp.95-106
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    • 2023
  • As artificial intelligence has become commonplace in various fields, the transparency of AI in its development and implementation has become an important issue. In safety-critical areas, the eXplainable and/or understandable of artificial intelligence is being actively studied. On the other hand, machine learning have been applied to the intelligence of self-organizing network (SON), but transparency in this application has been neglected, despite the critical decision-makings in the operation of mobile communication systems. We describes concepts of eXplainable machine learning (ML), along with research trends, major issues, and research directions. After summarizing the ML research on SON, research directions are analyzed for explainable ML required in intelligent SON of beyond 5G and 6G communication.

강북구 148마을의 건강주민운동으로서 발전가능요인 (Success factors for the Development of Health Community Organizing in: 148 Village, Gangbuk-gu, Seoul)

  • 홍종원;김준형;이순희;김남준;박웅섭
    • 농촌의학ㆍ지역보건
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    • 제47권3호
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    • pp.154-165
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    • 2022
  • 이 연구는 정부지원이 중단된 이후에도 건강주민운동이 발전해 나아간 과정과 강북구 건강주민운동의 단계별 특징을 분석하고 발전가능요인을 도출하는 것을 목적으로 수행되었다. 연구의 대상은 강북구 148번지에서 일어난 건강주민운동에 실제로 참여하였으며 주된 역할을 수행하였던 참여자들이다. 건강주민운동의 진행과정, 주민주도성, 건강주민운동의 발전가능요인 등에 대하여 심층면접을 통해 조사하였다. 연구 결과, 정부지원이 중단된 이후에도 강북구 건강주민운동이 발전할 수 있었던 요인은 다음과 같다. 첫째, 세대를 넘나든 주민 관계가 형성되었다. 둘째, 주민의 이해관계에서 출발하였다. 셋째, 함께 해결할 수 있다는 믿음이 있었다. 넷째, 주민의 자발성을 바탕에 둔 외부지원이 있었다. 다섯째, 공공성에 기반하여 활동하였다. 여섯째, 지역에 기반한 주민 지도력을 발굴하였다. 외부의 지원 없이 주직조직화의 원칙을 따르는 건강주민운동은 지속 및 발전이 가능하며, 주민중심의 건강주민운동으로 발전하려면 이 연구에서 도출한 성공 요인을 반영할 필요가 있다.