• Convergence Security Journal
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• v.11 no.1
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• pp.11-18
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• 2011

Wireless mesh network technology with transmission speeds similar to wired and wireless technology means to build, compared with wired networks, building a more efficient network to provide convenience and flexibility. The wireless mesh network router nodes in the energy impact of the mobility is less constrained and has fewer features entail. However, the characteristics of various kinds due to network configuration settings and the choice of multiple paths that can occur when the system overhead and there are many details that must be considered. Therefore, according to the characteristics of these network routing technology that is reflected in the design and optimization of the network is worth noting. In this paper, a multi-path setting can be raised in order to respond effectively to the problem of the router node data loss and bandwidth according to traffic conditions and links to elements of the hop count evaluation by using a genetic algorithm as a workaround for dynamic routing the routing metric for wireless mesh network scheme is proposed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9A
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• pp.888-897
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• 2007

In this paper, we propose an uplink dynamic resource allocation algorithm to increase sector throughput and fairness among users in 802.16e OFDMA TDD system. In uplink, we address the difference between uplink and downlink channel state information in 802.16e OFDMA TDD system. The simulation results show that not only an increment of 10% of sector throughput but higher level of fairness is achieved by round-robin using the FLR and the rate / margin adaptive inner closed-loop power control algorithm. The FLR algorithm determines the number of sub-channels to be allocated to the user according to the user's position. Also, we get 31.8% more sector throughput compared with the round-robin using FLR by FASA algorithm using uplink channel state information. User selection, sub-channel allocation, power allocation algorithms and simulation methodology are mentioned in Part I.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1586-1592
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• 1999

In DWMT, CMFB is employed in the synthesis/analysis part. The CMFB uses filters of greater length than the DFT, resulting in reduced interference between the carriers. In addition, the CMFB system is computationally efficient and fast algorithms are available for their implementation. Traditional designs for the prototype filters of CMFB usually involve nonlinear optimizations. Thus the required design time is considerably large even for small filter orders. In this paper, a prototype filter design method for CMFB is presented using optimal window method. The design process is reduced to the optimization of a single parameter and consequently the required design time is much less than those of the existing methods. It is shown that the stopband performance of the proposed method is better than that of the Kaiser window method.

• KIEE International Transactions on Power Engineering
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• v.5A no.3
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• pp.269-279
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• 2005

This paper presents an application of the parallel Adaptive Evolutionary Algorithm (AEA) to search an optimal solution of a reconfiguration in distribution systems. The aim of the reconfiguration is to determine the appropriate switch position to be opened for loss minimization in radial distribution systems, which is a discrete optimization problem. This problem has many constraints and it is very difficult to find the optimal switch position because of its numerous local minima. In this investigation, a parallel AEA was developed for the reconfiguration of the distribution system. In parallel AEA, a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner are used in order to combine the merits of two different evolutionary algorithms: the global search capability of GA and the local search capability of ES. In the reproduction procedure, proportions of the population by GA and ES are adaptively modulated according to the fitness. After AEA operations, the best solutions of AEA processors are transferred to the neighboring processors. For parallel computing, a PC-cluster system consisting of 8 PCs·was developed. Each PC employs the 2 GHz Pentium IV CPU, and is connected with others through switch based fast Ethernet. The new developed algorithm has been tested and is compared to distribution systems in the reference paper to verify the usefulness of the proposed method. From the simulation results, it is found that the proposed algorithm is efficient and robust for distribution system reconfiguration in terms of the solution quality, speedup, efficiency, and computation time.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1043-1051
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• 2018

The coordination of directional overcurrent relay (DOCR) is employed in this work, considering gray wolf optimizer (GWO), a recently designed optimizer that employs the hunting and leadership attitude of gray wolves for searching a global optimum. In power system protection coordination problem, the objective function to be optimized is the sum of operating time of all the main relays. The coordination of directional overcurrent relays is formulated as a linear programming problem. The proposed optimization technique aims to minimize the time dial settings (TDS) of the relays. The calculation of the Time Dial Setting (TDS) setting of the relays is the core of the coordination study. In this article two case studies of IEEE 6-bus system and IEEE 30-bus system are utilized to see the efficiency of this algorithm and the results had been compared with the other algorithms available in the reference and it was observed that the proposed scheme is quite competent for dealing with such problems. From analyzing the obtained results, it has been found that the GWO approach provides the most globally optimum solution at a faster convergence speed. GWO has achieved a lot of relaxation due to its easy implementation, modesty and robustness. MATLAB computer programming has been applied to see the effectiveness of this algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.1
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• pp.6-13
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• 2002

This paper deals with the linear matrix inequality (LMI) design procedures for multi-objective Η$_2$/Η$_{\infty}$ controllers with pole-placement constraints for an inverted pendulum system modeled as convex polytopes to ensure the stabilizing regulator and tracking performances. Polytopic models with multiple linear time-invariant models linearized at some operating points are derived to design controllers overcoming the conservativeness such as a controller may have when it is designed for a model linearized at a single operating point. Multi-objective controllers are designed for polytopic models by the LMT design technique with convex algorithms. It is observed that the inverted pendulum controlled by any controller designed for each polytopic model is stabilizingly restored to the vertical angle position for initial values of larger tilt anlges.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.83-90
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• 2015

This paper proposes a Tabu search algorithm to maximize the connectivity between the router nodes and the client nodes in wireless mesh networks. As the number of the router nodes and the client nodes in the networks increases, the amount of calculation for finding the solution would be too much increased. To obtain the optimal solution within a reasonable computation time for a high-density network, we propose a Tabu search algorithm to obtain the optimal solution for maximizing the connectivity. In order to make a search more efficient, we propose some efficient neighborhood generating operations of the Tabu search algorithm. We evaluate those performances through some experiments in terms of the maximum number of the connectivity and the execution time of the proposed algorithm. The comparison results show that the proposed algorithm outperforms other existing algorithms.

• The KIPS Transactions:PartC
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• v.18C no.3
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• pp.179-186
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• 2011

Wireless Mesh Network technology refers to the technology which establishes wireless network whose transmission speed is similar to that of the wire system, and provides more enhanced flexibility in the building of network, compared to the existing wired network. In addition, it has the feature of less mobility and less restriction from the energy effect. However, there follow many considerations such as system overhead in the case of setting or the selection of multi-path. Accordingly, the focus is on the design and optimization of network which can reflect this network feature and the technology to establish path. This paper suggests the methods on the programming of path in Wireless Mesh Network routing by applying the evaluation value of node service, making use of the loss rate of data, the hop count of bandwidth and link and the traffic status of node, considering the performance of link and load in the fitness evaluation function, in order to respond to the programming of multi-path effectively.

• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.175-195
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• 2005

사례기반추론(case-based reasoning)은 사례간 유사도를 평가하여 유사한 이웃사례를 찾아내고, 이웃사례의 결과를 이용하여 새로운 사례에 대한 예측결과를 생성하는 전통적인 인공지능기법 중 하나다. 이러한 사례기반추론이 최근 적용이 쉽고 간단하다는 장점과 모형의 갱신이 실시간으로 이루어진다는 점 등으로 인해, 온라인 환경에서의 고객관계관리를 위한 도구로 학계와 실무에서 주목을 받고 있다 하지만, 전통적인 사례기반추론의 경우, 타 인공지능기법에 비해 정확도가 상대적으로 크게 떨어진다는 점이 종종 문제점으로 제기되어 왔다. 이에, 본 연구에서는 사례기반추론의 성과를 획기적으로 개선하기 위한 방법으로 유전자 알고리즘을 활용한 사례기반추론의 동시 최적화 모형을 제안하고자 한다. 본 연구가 제안하는 모형에서는 기존 연구에서 사례기반추론의 성과에 중대한 영향을 미치는 요소들로 제시된 바 있는 사례 특징변수의 상대적 가중치 선정(feature weighting)과 참조사례 선정(instance selection)을 유전자 알고리즘을 이용해 최적화함으로서, 사례간 유사도를 보다 정밀하게 도출하는 동시에 추론의 결과를 왜곡할 수 있는 오류사례의 영향을 최소화하고자 하였다. 제안모형의 유용성을 검증하기 위해, 본 연구에서는 국내 한 전문 인터넷 쇼핑몰의 구매예측모형 구축사례에 제안모형을 적용하여 그 성과를 살펴보았다. 그 결과, 제안모형이 지금까지 기존 연구에서 제안된 다른 사례기반추론 개선모형들은 물론, 로지스틱 회귀분석(LOGIT), 다중판별분석(MDA), 인공신경망(ANN), SVM 등 다른 인공지능 기법들에 비해서도 상대적으로 우수한 성과를 도출할 수 있음을 확인할 수 있었다.

• Journal of Korean Society of Steel Construction
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• v.19 no.2
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• pp.171-179
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• 2007

The greenhouse discrete optimum design program was developed using discrete optimum algorithm based on the genetic algorithm. The basic search method for the optimum design is the genetic algorithm, which is known to be very efficient for discrete optimization. In this paper, the objective function was the weight of the greenhouse structures and the constraints were the limits state design method. The design variables were galvanized steel pipes for plastic housing KSD 3760. Objective criteria were presented for the design of economic greenhouse structure and evaluation of its stability. The standardizations of greenhouse structure were used, as well as the normalization of greenhouse-related materials. Design examples were given to show the applicability of the optimum design using the discrete optimum algorithm based on the genetic algorithm of this study.