• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.9
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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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.2
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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.

• KIEE International Transaction on Systems and Control
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• v.12D no.1
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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.

• Journal of the Korean Institute of Rural Architecture
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• v.2 no.3
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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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.1 no.2
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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.

• Asia pacific journal of information systems
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• v.16 no.3
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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.

• Tuberculosis and Respiratory Diseases
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• v.84 no.3
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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.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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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.

• Electronics and Telecommunications Trends
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• v.38 no.6
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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.

• Journal of agricultural medicine and community health
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• v.47 no.3
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• pp.154-165
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• 2022

Objectives: The purpose of this study was to examine the success factors for the development of health community organizing in regard to its perspective in: 148 village, Gangbuk-gu, Seoul. Methods: We conducted a qualitative study using in-depth interviews from February 2020 to December 2021. Seven operators who had worked for the project were enrolled in this study. Results: In this study, the success factors for the development of health community organizing were analyzed as follows; building community relationships across generations; starting from interests of the community; belief that working together can solve the issues; external support based on spontaneity of community; project based on publicness; discovering community-based leadership. Conclusions: This study suggested that health community organizing following the principle of community organizing can sustain and develop itself without external support. In order to develop into resident-oriented health community organizing, it is necessary to reflect the success factors derived from this study.