• 융합신호처리학회논문지
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• 제4권3호
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• pp.49-54
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• 2003

본 논문에서는 PID 제어기 응답을 보상하기위해 자기구성 신경망 보상기를 추가한 제어기를 제안한다. 기존의 PID 제어기는 제어기 설계가 간단하나 계수값을 설정하는데 많은 시행착오가 필요하다. 그리고, 신경망 제어 방식은 여러 파라미터들을 설계자의 임의에 따라 결정함으로써 최적의 구조를 갖지 못하는 단점이 있다. 본 논문에서는 이러한 문제를 해결하기위해 역전파 알고리즘을 기본으로 하여 은닉계층 노드의 활성화 함수로 가우시안 포텐셜함수를 사용하는 자기구성 신경망을 사용해, PID 제어기의 출력을 보상하도록 하였다. 자기구성 신경망은 학습을 진행함에 따라 가우시안 함수의 위치와 모양, 갯수가 자동으로 조정 되도록 하였다. 자기구성 신경망 보상기를 추가한 PID 제어기의 성능을 확인하기 위해서 2차 플랜트에 적용하여 모의 실험하였으며 DSP 프로세서를 사용하여 제어기를 구현한 후 유압 서보시스템의 속도 제어에 적용하여 실험결과를 관찰하였다.

• 제어로봇시스템학회논문지
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• 제4권3호
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• pp.378-383
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• 1998

A FOV, that stands for "Field Of View", refers to the maximum area where a camera could be wholly seen. If a FOV of CCD camera cannot the cover overall inspection area, the overall inspection area should be divided into sub-areas of size FOV. In this paper, we propose a new neural network-based FOV generation method by using a newly modified self-organizing map(SOM) which has multiple structure based on a self-organizing map, and uses new training rule that is composed of the movement, creation and deletion terms. Then, experiment results using real PCB indicate the superiority of the method developed in this study to the existing sequential method.al method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1549-1552
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• 1997

In this paper, a optimal algorithm that can produce the FOV is proposed in terms of using the Kohonen's Self-Organizing Map(KSOM). A FOV, that stands for "Field Of View", means maximum area where a camera could be wholly seen and influences the total time of inspection of vision system. Therefore, we draw algorithm with a KSOM which aims to map an input space of N-dimensions into a one-or two-dimensional lattice of output layer neurons in order to optimize the number and location of FOV, instead of former sequentila method. Then, we show demonstratin through computer simulation using the real PCB data. PCB data.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2005년도 추계 학술대회논문집
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• pp.1-10
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• 2005

A new approach, Multi-Objective Design Exploration (MODE), is presented to address Multidisciplinary Design Optimization (MDO) problems by CFD-CSD coupling. MODE reveals the structure of the design space from the trade-off information and visualizes it as a panorama for Decision Maker. The present form of MODE consists of Kriging Model, Adaptive Range Multi Objective Genetic Algorithms, Analysis of Variance and Self-Organizing Map. The main emphasis of this approach is visual data mining. An MDO system using high fidelity simulation codes, Navier-Stokes solver and NASTRAN, has been developed and applied to a regional-jet wing design. Because the optimization system becomes very computationally expensive, only brief exploration of the design space has been performed. However, data mining result demonstrates that design knowledge can produce a good design even from the brief design exploration.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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• pp.800-802
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• 2000

In this paper, we propose the Self-Organizing Networks(SON) based on competitive Fuzzy Polynomial Neuron(FPN) for the optimal design of nonlinear process system. The SON architectures consist of layers with activation nodes based on fuzzy inference rules. Here each activation node is presented as FPN which includes either the simplified or regression Polynomial fuzzy inference rules. The proposed SON is a network resulting from the fusion of the Polynomial Neural Networks(PNN) and a fuzzy inference system. The conclusion part of the rules, especially the regression polynomial uses several types of high-order polynomials such as liner, quadratic and modified quadratic. As the premise part of the rules, both triangular and Gaussian-like membership functions are studied. Chaotic time series data used to evaluate the performance of our proposed model.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 정기총회 및 추계학술대회 논문집 학회본부
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• pp.23-25
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• 1993

This paper presents a design technique of self-organizing fuzzy controller using a learning method of fuzzy inference rule by a gradient method for load frequency control of power system. The membership functions in antecedent part and in consequent part of fuzzy inference rules are tuned by the gradient method. The related simulation results show that the proposed fuzzy controller are more powerful than the conventional ones for reduction of undershoot and deviation of load frequency in steady-state, and for minimization of settling time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제3권3호
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• pp.309-330
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• 2009

In this paper, we introduce the architecture of Genetic Algorithm(GA) based Feed-forward Polynomial Neural Networks(PNNs) and discuss a comprehensive design methodology. A conventional PNN consists of Polynomial Neurons, or nodes, located in several layers through a network growth process. In order to generate structurally optimized PNNs, a GA-based design procedure for each layer of the PNN leads to the selection of preferred nodes(PNs) with optimal parameters available within the PNN. To evaluate the performance of the GA-based PNN, experiments are done on a model by applying Medical Imaging System(MIS) data to a multi-variable software process. A comparative analysis shows that the proposed GA-based PNN is modeled with higher accuracy and more superb predictive capability than previously presented intelligent models.

• 전자공학회논문지B
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• 제33B권7호
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• pp.173-182
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• 1996

In this paper, we propose the parallel, self-organizing, hierarchical neural netowrks as a handwritten digit recognition system. This system can absorb the various shape variations of handwritten digits by using the different methods of extracting the features in each stage neural network (SNN) of the PSHNN, and can reduce training time by using the single layer neural network as the SNN, and can obtain high rate of correct recognition by using the certainty area in all the output nodes individually. experiments have been performed with NIST database. In which we use 21, 315 digits (10, 625 digits for training and 10,663 digits for testing). The results show that the correct rate is 97.48% the error rate is 1.72% and the reject rate is 0.78%.

• ETRI Journal
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• 제41권5호
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• pp.574-584
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• 2019

A new Mirai variant found recently was equipped with a dynamic update ability, which increases the level of difficulty for DDoS mitigation. Continuous development of 5G technology and an increasing number of Internet of Things (IoT) devices connected to the network pose serious threats to cyber security. Therefore, researchers have tried to develop better DDoS mitigation systems. However, the majority of the existing models provide centralized solutions either by deploying the system with additional servers at the host site, on the cloud, or at third party locations, which may cause latency. Since Internet service providers (ISP) are links between the internet and users, deploying the defense system within the ISP domain is the panacea for delivering an efficient solution. To cope with the dynamic nature of the new DDoS attacks, we utilized an unsupervised artificial neural network to develop a hierarchical two-layered self-organizing map equipped with a twofold feature selection for DDoS mitigation within the ISP domain.

• 한국통신학회논문지
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• 제40권7호
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• pp.1457-1467
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• 2015

해양 통신을 위한 VHF 대역 데이터 통신 시스템(VHF Data Exchange System: VDES)은 송수신단의 종류에 따라 서로 다른 주파수 대역을 사용하도록 설계되어 있으며, 육상국으로부터 멀리 떨어진 선박국에게 육상국과 연결성을 보장하기 위해 제안된 ASO-TDMA (Ad-hoc Self-Organizing TDMA) MAC 프로토콜을 이용하여 다중-홉 통신을 수행하는 경우에 주파수 채널간 부하 불균형 문제가 발생한다. 본 논문에서는 이러한 주파수 채널간 부하 불균형 문제를 해결하기 위해 통계적 기하(stochastic geometry) 모델링을 도입한다. 이를 기반으로 동일 홉 영역에서의 공간적 자원 재사용률을 분석하고, 각 홉 영역 별로 최적의 자원 할당을 통해 채널간의 부하 불균형 문제를 해결하여 자원 활용도를 극대화하는 것을 보인다.