• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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• pp.572-574
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• 1998

In this paper, we are proposed design of ATM networks to transfer for electric power system informations, proposed transport networks is partitioned management part and functional part, management part is partitioned edge network, core network, local network, authority network, functional part is partitioned core network, access network, edge area. It is based on laying and partitioning by ITU-T G.805, we also proposed ATM network requirements for Carrier Relay traffic acceptability in electric power system information.

• 응용통계연구
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• 제35권2호
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• pp.299-310
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• 2022

사회 네트워크 분석에 대한 관심이 높아짐에 따라 사회 네트워크에서 발생하는 변화를 탐지하는 연구에 대한 관심도 높아지고 있다. 사회 네트워크에서 발생하는 변화는 네트워크의 구조적 변화로 나타난다. 따라서 사회 네트워크에서 발생하는 변화를 탐지하는 것은 네트워크의 구조적 특성에 대한 변화를 탐지하는 것이다. 사회 네트워크에서 발생하는 지역적 변화는 가까운 이웃들 간에 발생하는 변화로 네트워크 일부에 집단적으로 나타난다. 이 논문의 목적은 네트워크에서 발생하는 지역적 변화를 효율적으로 탐지하는 절차를 제안하는 것이다. 제안하는 절차는 지역적 변화를 보다 효율적으로 탐지하기 위해 네트워크를 분할하고 각각의 분할된 네트워크에 기반한 관리도를 작성하여 네트워크에서 발생한 변화를 탐지하는 것이다. 네트워크를 분할하여 변화를 탐지하는 절차는 네트워크에서 발생한 지역적 변화를 보다 신속하게 탐지할 수 있으며, 변화가 발생한 위치에 대한 정보를 제공한다는 장점이 있다. 모의실험 결과에 따르면 제안된 절차는 네트워크의 크기가 작고 변화의 크기가 작은 경우 효율적이며, 네트워크를 더 작은 크기로 분할하면 작은 변화를 더 효율적으로 탐지한다는 사실을 확인하였다.

• 전자공학회논문지B
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• 제33B권10호
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• pp.107-119
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• 1996

In this paper, we propose multiple component neural network(MCNN) which learn partitioned patterns in each multiple component neural networks by reducing dimensions of input pattern vector using PCA (principal component analysis). Procesed neural network use Oja's rule that has a role of PCA, output patterns are used a slearning patterns on small component neural networks and we call it CBP. For simply not solved patterns in a network, we solves it by regenerating new CBP neural networks and by performing dynamic partitioned pattern learning. Simulation results shows that proposed MCNN neural networks are very small size networks and have very fast learning speed compared with multilayer neural network EBP.

• 정보처리학회논문지C
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• 제16C권4호
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• pp.521-526
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• 2009

DTN(Disruption/Delay Tolerant Network)은 네트워크의 단절성(partitioning)이 높은 환경에서 단절된 지역 네트워크를 연동하기 위한 네트워크 구조이다. 현재 DTN과 관련하여 많은 연구가 이루어지고 있으며 특히 라우팅 기법에 대한 연구는 가장 많은 관심을 받는 분야 중 하나이다. 본 논문에서는 단절된 애드혹(Ad-hoc) 네트워크에서 사용자간의 연결성을 제공하기 위하여 무인항공기(Unmanned Aerial Vehicle: UAV)를 이용한 DTN의 구성 시 사용가능한 DTN 라우팅 기법을 살펴보고 UAV의 이동 경로 제어 기법을 제안한다. 또한 다양한 시나리오에서의 실험을 통하여 제안된 방법의 성능을 평가한다.

• Journal of Information Technology Applications and Management
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• 제14권2호
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• pp.151-168
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• 2007

The corporate credit rating represents an assessment of the relative level of risk associated with the timely payments required by the debt obligation. In this study, the corporate credit rating model employs artificial intelligence methods including Neural Network (NN) and Case-Based Reasoning (CBR). At first we suggest three classification models, as partitioned neural networks, all of which convert multi-group classification problems into two group classification ones: Ordinal Pairwise Partitioning (OPP) model, binary classification model and simple classification model. The experimental results show that the partitioned NN outperformed the conventional NN. In addition, we put to use CBR that is widely used recently as a problem-solving and learning tool both in academic and business areas. With an advantage of the easiness in model design compared to a NN model, the CBR model proves itself to have good classification capability through the highest hit ratio in the corporate credit rating.

• International journal of advanced smart convergence
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• 제1권2호
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• pp.30-33
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• 2012

This paper propose a new design of fuzzy neural networks based on hard partition to generate the rules of the networks. For this we use hard c-means (HCM) clustering algorithm. The premise part of the rules of the proposed networks is realized with the aid of the hard partition of input space generated by HCM clustering algorithm. The consequence part of the rule is represented by polynomial functions. And the coefficients of the polynomial functions are learned by BP algorithm. The number of the hard partition of input space equals the number of clusters and the individual partitioned spaces indicate the rules of the networks. Due to these characteristics, we may alleviate the problem of the curse of dimensionality. The proposed networks are evaluated with the use of numerical experimentation.

• Journal of information and communication convergence engineering
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• 제7권2호
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• pp.141-147
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• 2009

To initialize and maintain self-organizing networks such as mobile ad hoc networks, address allocation protocol is essentially required. However, centralized approaches that pervasively used in traditional networks are not recommended in this kind of networks since they cannot handle with mobility efficiently. In addition, previous distributed approaches suffer from inefficiency with control overhead caused by duplicated address detection and management of available address pool. In this paper, we propose a new dynamic address allocation scheme, which is based on adaptive partition. An available address is managed in distributed way by multiple agents and partitioned adaptively according to current network environments. Finally, simulation results reveal that a proposed scheme is superior to previous approach in term of address acquisition delay under diverse simulation scenarios.

• 디지털융복합연구
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• 제10권4호
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• pp.199-206
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• 2012

최근에 무선 모바일 네트워크상에서 모바일 클라이언트 요청증가로 인하여 스트리밍 미디어 객체를 관리하고 서비스하기 위한 새로운 기법이 제안되고 있다. 본 논문에서는 무선 모바일 네트워크상에서 스트리밍 미디어 서비스의 성능을 향상시키기 위한 새로운 객체 세그먼트 그룹화 방법을 제안한다. 제안된 기법은 분할된 객체 세그먼트들에 대해서 유사성 척도를 수행하며, 유사성 척도를 위해 disjunction, conjunction, 그리고 filtering연산을 수행한다. 이들 연산 척도에 따라 분할된 세그먼트들의 그룹화가 결정되며, 스트리밍 미디어 서비스 성능이 결정된다. 시뮬레이션 결과 제안된 기법은 처리율, 평균 시작지연, 그리고 캐시 히트율의 성능이 우수함을 보였다.

• 한국CDE학회논문집
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• 제2권2호
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• pp.77-84
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• 1997

This paper is concerning the development of multiple neural networks system of problem domains where the complete input space can be decomposed into several different regions, and these are known prior to training neural networks. We will adopt oblique decision tree to represent the divided input space and sel ect an appropriate subnetworks, each of which is trained over a different region of input space. The overall architecture of multiple neural networks system, called the federated architecture, consists of a facilitator, normal subnetworks, and tile networks. The role of a facilitator is to choose the subnetwork that is suitable for the given input data using information obtained from decision tree. However, if input data is close enough to the boundaries of regions, there is a large possibility of selecting the invalid subnetwork due to the incorrect prediction of decision tree. When such a situation is encountered, the facilitator selects a tile network that is trained closely to the boundaries of partitioned input space, instead of a normal subnetwork. In this way, it is possible to reduce the large error of neural networks at zones close to borders of regions. The validation of our approach is examined and verified by applying the federated neural networks system to the configuration design of a midship structure.

• 한국통신학회논문지
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• 제32권10A호
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• pp.1004-1014
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• 2007

In sensor networks, it is crucial to reliably and energy-efficiently deliver sensed information from each source to a sink node. Specifically, in mobile sink (user) applications, due to the sink mobility, a stationary dissemination path may no longer be effective. The path will have to be continuously reconfigured according to the current location of the sink. Moreover, the dynamic optimal path from each source to the sink is required in order to reduce end-to-end delay and additional energy wastage. In this paper, an Adaptive Reversal Optimal path Tree (AROT) protocol is proposed. Information delivery from each source to a mobile sink can be easily achieved along the AROT without additional control overhead, because the AROT proactively performs adaptive sink mobility management. In addition, the dynamic path is optimal in terms of hop counts and the AROT can maintain a robust tree structure by quickly recovering the partitioned tree with minimum packet transmission. Finally, the simulation results demonstrate that the AROT is a considerably energy-efficient and robust protocol.