• IEIE Transactions on Smart Processing and Computing
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• 제1권1호
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• pp.27-33
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• 2012

The Ethernet Passive Optical Network (EPON) has been considered to be one of the most promising solutions for the implementation of the Fiber To The Home (FTTH) technology designed to ameliorate the "last mile" bandwidth bottleneck. In the EPON network, an efficient and fair bandwidth allocation is a very important issue, since multiple optical network units (ONUs) share a common upstream channel for packet transmission. To increase bandwidth utilization, an EPON system must provide a way to adaptively allocate the upstream bandwidth among multiple ONUs in accordance to their bandwidth demands and requirements. We present a new hybrid method that satisfies these requirements. The advantage of our method comes from the consideration of application-specific bandwidth allocation and the minimization of the idle bandwidth. Our simulation results show that our proposed method outperforms existing dynamic bandwidth allocation methods in terms of bandwidth utilization.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.176-178
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• 2004

Precise control of interior permanent magnet synchronous motor(IPMSM) over wide speed range is an engineering challenge. This paper considers the design and implementation of novel technique of speed estimation and control for IPMSM using hybrid intelligent control. The hybrid combination of neural network and adaptive fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of IPMSM using adaptive neural network fuzzy(A-NNF) and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed.

• 전자공학회논문지C
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• 제34C권7호
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• pp.70-81
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• 1997

In this paper, we propose HMCNN(hybrid multiple component neural networks) that enhance performance of MCNN by adapting new pattern partitioning algorithm which can cluster many input patterns efficiently. Added neural network performs similar learning procedure that of kohonen network. But it dynamically determine it's number of output neurons using algorithms that decide self-organized number of clusters and patterns in a cluster. The proposed network can effectively be applied to problems of large data as well as huge networks size. As a sresutl, proposed pattern partitioning network can enhance performance results and solve weakness of MCNN like generalization capability. In addition, we can get more fast speed by performing parallel learning than that of other supervised learning networks.

• 통합자연과학논문집
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• 제1권3호
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• pp.210-215
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• 2008

Ad hoc network는 무선 노드들의 집합으로서 어떤 인프라스트럭처 도움 없이 그들 서로가 multi-hop 경로를 통해 통신한다. 본 논문에서는 ad hoc network에서 사용되는 proactive 라우팅 프로토콜과 on-demand 라우팅 프로토콜의 혼합인 hybrid 라우팅 프로토콜에 대해 제안하였다. 본 논문에서는 기존의 hybrid 라우팅 프로토콜인 ZRP와는 달리 Ad hoc network를 구성하는 노드들 중에 네트워크 서비스를 제공해주는 특별한 노드를 설정하여 라우팅 하는 방법을 제안한다. 이러한 역할을 해주는 특별한 노드를 본 논문에서는 C-Node라 부른다. C-Node를 이용한 라우팅으로 기존의 라우팅 프로토콜보다 경로 설정 시간과 flooding 시간을 줄이므로서 효율적인 라우팅을 수행할 수 있게된다.

• Asia pacific journal of information systems
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• 제5권1호
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• pp.36-51
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• 1995

본 논문에서는 비구조적인 의사결정문제를 효과적으로 해결하기 위하여 감독학습 인공신경망 모형과 비감독학습 인공신경망 모형을 결합한 하이브리드 인공신경망 모형인 HYNEN(HYbrid NEural Network) 모형을 제안한다. HYNEN모형은 주어진 자료를 클러스터화 하는 CNN(Clustering Neural Network)과 최종적인 출력을 제공하는 ONN(Output Neural Network)의 2단계로 구성되어 있다. 먼저 CNN에서는 주어진 자료로부터 적정한 퍼지규칙을 찾기 위하여 클러스터를 구성한다. 그리고 이러한 클러스터를 지식베이스로하여 ONN에서 최종적인 의사결정을 한다. CNN에서는 SOFM(Self Organizing Feature Map)과 LVQ(Learning Vector Quantization)를 클러스터를 만든 후 역전파학습 인공신경망 모형으로 이를 학습한다. ONN에서는 역전파학습 인공신경망 모형을 이용하여 각 클러스터의 내용을 학습한다. 제안된 HYNEN 모형을 우리나라 기업의 도산자료에 적용하여 그 결과를 다변량 판별분석법(MDA:Multivariate Discriminant Analysis)과 ACLS(Analog Concept Learning System) 퍼지 ARTMAP 그리고 기존의 역전파학습 인공신경망에 의한 실험결과와 비교하였다.

• 한국통신학회논문지
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• 제8권2호
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• pp.43-47
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• 1983

FIR필터와 IIR필터를 각각 독립적으로 설계하여 결합한 혼성 FIR/IIR필터에 의하여 이산신호의 보간을 위한 다상회로를 설계하였다. 제안된 다상회로는 백색 가우시안 잡음을 이용한 평가방법을 통하여 이산신호의 보간 필터로서의 유용성이 확인되었다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2004년도 봄 학술발표논문집 Vol.31 No.1 (A)
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• pp.430-432
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• 2004

Multicasting is an efficient means of one to many (or many to many) communications. Due to the frequent and unpredictable topology changes, multicast still remains as challenge and no one-size-fits-all protocol could serve all kinds of needs in ad hoc network. Protocols and approaches currently proposed on this issue could be classified mainly into four categories, tree-based, meshed-based, statelessness and hybrid. In this article, we borrow the concept of Eulerian ring in graph theory and propose a novel ring-based multicast framework--Hierarchical Eulerian Ring-Oriented Multicast Architecture (HEROMA) over wireless mobile Ad hoc network. It is familiar with hybrid protocol based on mesh and tree who concentrates on efficiency and robustness simultaneously. Architecture and recovery algorithm of HEROMA are investigated in details. Simulation result is also presented, which show different level of improvements on end-to-end delay in scenario of small scale.

• ETRI Journal
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• 제33권5호
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• pp.704-711
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• 2011

This paper proposes hybrid distributed stochastic addressing (HDSA), which combines the advantages of distributed addressing and stochastic addressing, to solve the problems encountered when constructing a network in a ZigBee-based wireless sensor network. HDSA can assign all the addresses for ZigBee beyond the limit of addresses assigned by the existing distributed address assignment mechanism. Thus, it can make the network scalable and can also utilize the advantages of tree routing. The simulation results reveal that HDSA has better addressing performance than distributed addressing and better routing performance than other on-demand routing methods.

• 대한안전경영과학회지
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• 제14권1호
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• pp.137-145
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• 2012

In the previous study, the construction guide line of IT infra-structure for a u-City was introduced. However, it is only concentrated on the components and construction procedure for provider-oriented and technology-oriented sensor networks. In this paper the architecture and building process of demander-oriented sensor networks for sustainable u-City service are proposed. In the paper it is described (1) the enhancement methods of the procedure that can be flexibly constructed according to the scale of the project, (2) the methods that can improve the structure from the wireless sensor network such as RFID/USN to the hybrid sensor network, and (3) the consideration factors for providing the sustainable u-City service.

• 한국환경과학회지
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• 제24권8호
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• pp.1023-1036
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• 2015

A reliable streamflow forecasting is essential for flood disaster prevention, reservoir operation, water supply and water resources management. This study proposes a hybrid model for river stage forecasting and investigates its accuracy. The proposed model is the wavelet packet-based artificial neural network(WPANN). Wavelet packet transform(WPT) module in WPANN model is employed to decompose an input time series into approximation and detail components. The decomposed time series are then used as inputs of artificial neural network(ANN) module in WPANN model. Based on model performance indexes, WPANN models are found to produce better efficiency than ANN model. WPANN-sym10 model yields the best performance among all other models. It is found that WPT improves the accuracy of ANN model. The results obtained from this study indicate that the conjunction of WPT and ANN can improve the efficiency of ANN model and can be a potential tool for forecasting river stage more accurately.