• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 하계학술대회 논문집
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• pp.333-336
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• 1991

In this paper, Hopfield & Tank model-like artificial neural network structure is proposed, which can be used for the optimal path planning problems such as the unit commitment problems or the maintenance scheduling problems which have been solved by the dynamic programming method or the branch and bound method. To construct the structure of the neural network, an energy function is defined, of which the global minimum means the optimal path of the problem. To avoid falling into one of the local minima during the optimization process, the simulated annealing method is applied via making the slope of the sigmoid transfer functions steeper gradually while the process progresses. As a result, computer(IBM 386-AT 34MHz) simulations can finish the optimal unit commitment problem with 10 power units and 24 hour periods (1 hour factor) in 5 minites. Furthermore, if the full parallel neural network hardware is contructed, the optimization time will be reduced remarkably.

• 한국정보통신학회논문지
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• 제5권4호
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• pp.756-765
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• 2001

An effective dexterous motion control method of redundant robot manipulators based on neural optimization network is proposed to satisfy multi-criteria such as singularity avoidance, minimizing energy consumption, and avoiding physical limits of actuator, while performing a given task. The method employs a neural optimization network with parallel processing capability, where only a simple geometric analysis for resolved motion of each joint is required instead of computing of the Jacobian and its pseudo inverse matrix. For dexterous motion, a joint geometric manipulability measure(JGMM) is proposed. JGMM evaluates a contribution of each joint differential motion in enlarging the length of the shortest axis among principal axes of the manipulability ellipsoid volume approximately obtained by a geometric analysis. Redundant robot manipulators is then controlled by neural optimization networks in such a way that 1) linear combination of the resolved motion by each joint differential motion should be equal to the desired velocity, 2) physical limits of joints are not violated, and 3) weighted sum of the square of each differential joint motion is minimized where weightings are adjusted by JGMM. To show the validity of the proposed method, several numerical examples are illustrated.

• 대한기계학회논문집A
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• 제27권7호
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• pp.1110-1119
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• 2003

This paper deals with the synthesis of the 3-dimensional grasp planning for unknown objects. Previous studies have many problems, which the estimation time for finding the grasping points is much long and the analysis used the not-perfect 3-dimensional modeling. To overcome these limitations in this paper new algorithm is proposed, which algorithm is achieved by two steps. First step is to find the whole 3-dimensional geometrical modeling for unknown objects by using stereo matching. Second step is to find the optimal grasping points for unknown objects by using the neural network trained by the result of optimization using genetic algorithm. The algorithm is verified by computer simulation, comparing the result between neural network and optimization.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권2호
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• pp.932-945
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• 2018

Everything in the world is becoming connected and interactive due to the Internet. The future of interactive smart environments such as smart cities, smart industries, or smart farms demand high network bandwidth, high network flexibility, and self-organization systems without costly hardware upgrades, and they provide a sustainable, scalable, and replicable smart environment backbone infrastructure. This paper presents a new Hybrid Software-Defined architecture for integrating Internet-of-Things technologies that are essential technologies for smart environments. It combines a software-defined networking infrastructure and a real-time distributed network framework with an advanced optimization to enable self-configuration, self-management, and self-adaption for providing seamless communication and efficiently managing a vast number of smart heterogeneous devices.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2011년도 제43차 동계학술발표논문집 19권1호
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• pp.307-310
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• 2011

IPTV의 스트리밍 서비스를 위해 P2P를 이용하는 방법이 활발하게 연구되어지고 있다. 이 논문에서는 topology를 최적화하는 방안으로 P2P에서 각 peer 간에 연결 및 전송 정보를 이용하는 방법을 제안한다. 제안하는 방법은 mesh-network에서 각 peer에 연결된 link의 수를 이용하여 업로드 대역폭을 추정하는 알고리즘을 기반으로 한다. 이 방법은 자원의 관리를 위해 업로드 대역폭을 판단하기 위한 메시지 과부하를 효과적으로 줄여주지만 스트리밍에서 주어진 연산만을 수행할 경우 업로드 대역폭과 무관한 형태로 network topology가 잘못 구성될 가능성을 가지고 있다. 본 논문에서는 기존 연구에서 부족했던 부분들을 정리하고 극복할 수 있는 각각의 알고리즘들과 적용했을 시에 예상되는 결과를 제시한다.

• International Journal of Control, Automation, and Systems
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• 제6권6호
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• pp.915-927
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• 2008

Networked control systems(NCSs) have gained increasing attention in recent years due to their advantages and potential applications. The network Quality-of-Service(QoS) in NCSs always fluctuates due to changes of the traffic load and available network resources. To handle the network QoS variations problem, this paper presents an intelligent scheduling control method for NCSs, where the sampling period and the control parameters are simultaneously scheduled to compensate the effect of QoS variation on NCSs performance. For NCSs with network-induced delays and packet dropouts, a discrete-time switch model is proposed. By defining a sampling-period-dependent Lyapunov function and a common quadratic Lyapunov function, the stability conditions are derived for NCSs in terms of linear matrix inequalities(LMIs). Based on the obtained stability conditions, the corresponding controller design problem is solved and the performance optimization problem is also investigated. Simulation results are given to demonstrate the effectiveness of the proposed approaches.

• International Journal of Computer Science & Network Security
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• 제22권3호
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• pp.236-244
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• 2022

Network Mobility Basic Support (NEMO BS) protocol has been accredited and approved by Internet Engineering Task Force (IETF) working group for mobility of sub-networks. Trains, aircrafts and buses are three examples of typical applications for this protocol. The NEMO BS protocol was designed to offer Internet access for a group of passengers in a roaming vehicle in an adequate fashion. Furthermore, in NEMO BS protocol, specific gateways referred to Mobile Routers (MRs) are responsible for carrying out the mobility management operations. Unfortunately, the main limitations of this basic solution are pinball suboptimal routing, excessive signaling cost, scalability, packet delivery overhead and handoff latency. In order to tackle shortcomings of triangular routing and Quality of Service (QoS) deterioration, the proposed scheme (Diff-FH NEMO) has previously evolved for end-users in moving network. In this sense, the article focuses on an exhaustive analytic evaluation at Home Agent (HA) entity of the proposed solutions. An investigation has been conducted on the signaling costs to assess the performance of the proposed scheme (Diff-FH NEMO) in comparison with the standard NEMO BS protocol and MIPv6 based Route Optimization (MIRON) scheme. The obtained results demonstrate that, the proposed scheme (Diff-FH NEMO) significantly improves the signaling cost at the HA entity in terms of the subnet residence time, number of mobile nodes, the number of DMRs, the number of LFNs and the number of CNs.

• 전자공학회논문지
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• 제50권5호
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• pp.18-24
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• 2013

네트워크 코딩은 브로드캐스트와 오버히어링 특성을 통해 네트워크의 처리율 향상을 가져오는 기법으로 널리 연구되고 있다. 본 논문에서는 인트라세션 네트워크 코딩 방법을 사용하여 멀티채널, 멀티라디오, 멀티세션으로 구성된 무선 멀티홉 네트워크 환경의 네트워크 유틸리티 향상을 위한 네트워크 유틸리티 최대화 문제를 모델링한다. 그리고 주어진 환경에서의 유틸리티 최대화 문제의 해를 구하기 위해 혼잡 제어 알고리즘, 분산 레이트 제어 알고리즘 그리고 휴리스틱 자원 할당 알고리즘을 제안한다. MATLAB을 사용하여 제안한 알고리즘에 대한 성능 평가를 하였으며 멀티채널, 멀티라디오, 멀티세션의 변화에 따른 네트워크 유틸리티를 구하였다. 그 결과, 제안한 세 가지 알고리즘을 통해 무선 멀티홉 네트워크에서 처리율 향상이 이루어짐을 알 수 있으며 본 논문에서 제안한 알고리즘을 통해 네트워크 처리율 최적화 문제에 대한 솔루션을 제시하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권1호
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• pp.7-12
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• 2003

In recent years, many attempts have been made to predict the behavior of bonds, currencies, stock or other economic markets. Most previous experiments used the neural network models for the stock market forecasting. The KOSPI 200 (Korea Composite Stock Price Index 200) is modeled by using different neural networks and fuzzy logic. In this paper, the neural network, the dynamic polynomial neural network (DPNN) and the fuzzy logic employed for the prediction of the KOSPI 200. The prediction results are compared by the root mean squared error (RMSE) and scatter plot, respectively. The results show that the performance of the fuzzy system is little bit worse than that of the DPNN but better than that of the neural network. We can develop the desired fuzzy system by optimization methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권12호
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• pp.3416-3435
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• 2023

Task offloading in vehicular networks is hot topic in the development of autonomous driving. In these scenarios, due to the role of vehicles and pedestrians, task characteristics are changing constantly. The classical deep learning algorithm always uses a pre-trained neural network to optimize task offloading, which leads to system performance degradation. Therefore, this paper proposes a neural network fine-tuning task offloading algorithm, combining with location prediction for pedestrians and vehicles by the Payne model of fluid dynamics and the car-following model, respectively. After the locations are predicted, characteristics of tasks can be obtained and the neural network will be fine-tuned. Finally, the proposed algorithm continuously predicts task characteristics and fine-tunes a neural network to maintain high system performance and meet low delay requirements. From the simulation results, compared with other algorithms, the proposed algorithm still guarantees a lower task offloading delay, especially when congestion occurs.