• Title/Summary/Keyword: Heuristic Function

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A Modulation and Channel State Estimation Algorithm Using the Received Signal Analysis in the Blind Channel (블라인드 채널에서 수신 신호 분석 기법을 사용한 변조 및 채널 상태 추정 알고리즘)

  • Cho, Minhwan;Nam, Haewoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.11
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    • pp.1406-1409
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    • 2016
  • In this paper, we propose the heuristic signal grouping algorithm to estimate channel state value over full blind communication situation which means that there is no information about the modulation scheme and the channel state information between the transmitter and the receiver. Hereafter, using the constellation rotation method and the probability density function(pdf) the modulation scheme is determined to perform automatic modulation classification(AMC). Furthermore, the modulation type and a channel state value estimation capability is evaluated by comparing the proposed scheme with other conventional techniques from the simulation results in terms of the symbol error rate(SER) and the root mean square error (RMSE).

Traffic Signal Control with Fuzzy Membership Functions Generated by Genetic Algorithms (유전 알고리즘에 의해 생성된 퍼지 소속함수를 갖는 교통 신호 제어)

  • Kim, Jong-Wan;Kim, Byeong-Man;Kim, Ju-Youn
    • Journal of the Korean Institute of Intelligent Systems
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    • v.8 no.6
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    • pp.78-84
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    • 1998
  • In this paper, a fuzzy traffic controller using genetic algorithms is presented. Conventional fuzzy traffic controllers use membership functions generated by humans. However, this approach does not guarantee the optimal solution to design the fuzzy controller. Genetic algorithm is a good problem solving method requiring domain-specific knowledge that is often heuristic. To find fuzzy membership functions showing good performance, a fitness function must be defined. However it's not easy in traffic control to define such a function as a numeric expression. Thus, we use simulation approach, namely, the fitness value of a solution is determined by use of a performance measure that is obtained by traffic simulator. The proposed method outperforms the conventional fuzzy controllers.

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Delay-Margin based Traffic Engineering for MPLS-DiffServ Networks

  • Ashour, Mohamed;Le-Ngoc, Tho
    • Journal of Communications and Networks
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    • v.10 no.3
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    • pp.351-361
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    • 2008
  • This paper presents a delay-margin based traffic engineering (TE) approach to provide end-to-end quality of service (QoS) in multi-protocol label switching (MPLS) networks using differentiated services (DiffServ) at the link level. The TE, including delay, class, and route assignments, is formulated as a nonlinear optimization problem reflecting the inter-class and inter-link dependency introduced by DiffServ and end-to-end QoS requirements. Three algorithms are used to provide a solution to the problem: The first two, centralized offline route configuration and link-class delay assignment, operate in the convex areas of the feasible region to consecutively reduce the objective function using a per-link per-class decomposition of the objective function gradient. The third one is a heuristic that promotes/demotes connections at different links in order to deal with concave areas that may be produced by a trunk route usage of more than one class on a given link. Approximations of the three algorithms suitable for on-line distributed TE operation are also derived. Simulation is used to show that proposed approach can increase the number of users while maintaining end-to-end QoS requirements.

Path Planning of Autonomous Guided Vehicle Using fuzzy Control & Genetic Algorithm (유전자 알고리즘과 퍼지 제어를 적용한 자율운송장치의 경로 계획)

  • Kim, Yong-Gug;Lee, Yun-Bae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.4 no.2
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    • pp.397-406
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    • 2000
  • Genetic algorithm is used as a means of search, optimization md machine learning, its structure is simple but it is applied to various areas. And it is about an active and effective controller which can flexibly prepare for changeable circumstances. For this study, research about an action base system evolving by itself is also being considered. There is to have a problem that depended entirely on heuristic knowledge of expert forming membership function and control rule for fuzzy controller design. In this paper, for forming the fuzzy control to perform self-organization, we tuned the membership function to the most optimal using a genetic algorithm(GA) and improved the control efficiency by the self-correction and generation of control rules.

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Virtual Network Embedding based on Node Connectivity Awareness and Path Integration Evaluation

  • Zhao, Zhiyuan;Meng, Xiangru;Su, Yuze;Li, Zhentao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.7
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    • pp.3393-3412
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    • 2017
  • As a main challenge in network virtualization, virtual network embedding problem is increasingly important and heuristic algorithms are of great interest. Aiming at the problems of poor correlation in node embedding and link embedding, long distance between adjacent virtual nodes and imbalance resource consumption of network components during embedding, we herein propose a two-stage virtual network embedding algorithm NA-PVNM. In node embedding stage, resource requirement and breadth first search algorithm are introduced to sort virtual nodes, and a node fitness function is developed to find the best substrate node. In link embedding stage, a path fitness function is developed to find the best path in which available bandwidth, CPU and path length are considered. Simulation results showed that the proposed algorithm could shorten link embedding distance, increase the acceptance ratio and revenue to cost ratio compared to previously reported algorithms. We also analyzed the impact of position constraint and substrate network attribute on algorithm performance, as well as the utilization of the substrate network resources during embedding via simulation. The results showed that, under the constraint of substrate resource distribution and virtual network requests, the critical factor of improving success ratio is to reduce resource consumption during embedding.

An Arrangement Technique for Fine Regular Triangle Grid of Network Dome by Using Harmony Search Algorithm (화음탐색 알고리즘을 이용한 네트워크 돔의 정삼각형 격자 조절기법)

  • Shon, Su-Deok;Jo, Hye-Won;Lee, Seung-Jae
    • Journal of Korean Association for Spatial Structures
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    • v.15 no.2
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    • pp.87-94
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    • 2015
  • This paper aimed at modeling a fine triangular grid for network dome by using Harmony Search (HS) algorithm. For this purpose, an optimization process to find a fine regular triangular mesh on the curved surface was proposed and the analysis program was developed. An objective function was consist of areas and edge's length of each triangular and its standard deviations, and design variables were subject to the upper and lower boundary which was calculated on the nodal connectivity. Triangular network dome model, which was initially consist of randomly irregular triangular mesh, was selected for the target example and the numerical result was analyzed in accordance with the HS parameters. From the analysis results of adopted model, the fitness function has been converged and the optimized triangular grid could be obtained from the initially distorted network dome example.

Small Base Station Association and Cooperative Receiver Design for HetNets via Distributed SOCP

  • Lu, Li;Wang, Desheng;Zhao, Hongyi;Liu, Yingzhuang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.12
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    • pp.5212-5230
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    • 2016
  • How to determine the right number of small base stations to activate in multi-cell uplinks to match traffic from a fixed quantity of K users is an open question. This paper analyses the uplink cooperative that jointly receives base stations activation to explore this question. This paper is different from existing works only consider transmitting power as optimization objective function. The global objective function is formulated as a summation of two terms: transmitting power for data and coordinated overhead for control. Then, the joint base stations activation and beamforming problem is formulated as a mixed integer second order cone optimization. To solve this problem, we develop two polynomial-time distributed methods. Method one is a two-stage solution which activates no more than K small base stations (SBSs). Method two is a heuristic algorithm by dual decomposition to MI-SOCP that activates more SBSs to obtain multiple-antennae diversity gains. Thanks to the parallel computation for each node, our methods are more computationally efficient. The strengths and weaknesses of these two proposed two algorithms are also compared using numerical results.

A Study on the Optimal Design Fuzzy Type Stabilizing Controller using Genetic Algorithm (유전 알고리즘을 이용한 퍼지형 안전화 제어기의 최적 설계에 관한 연구)

  • Lee, Heung-Jae;Lim, Chan-Ho;Yoon, Byong-Gyu;Lim, Hwa-Young;Song, Ja-Youn
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.11
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    • pp.1382-1387
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    • 1999
  • This paper presents an optimal fuzzy power system stabilizer to damp out low frequency oscillation. So far fuzzy controllers have been applied to power system stabilizing controllers due to its excellent properties on the nonlinear systems. But the design process of fuzzy logic power system stabilizer requires empirical and heuristic knowledge of human experts as well as many trial-and-errors in general. This paper presents and optimal design method of the fuzzy logic stabilizer using the genetic algorithm. Non-symmetric membership functions are optimally tuned over an evaluation function. The present inputs of fuzzy stabilizer are torque angle error and the change of torque angle error without loss of generality. The coding method used in this paper is concatenated binary mapping. Each linguistic fuzzy variable, defined as the peak of a membership function, is assigned by the mapping from a minimum value to a maximum value using eight bits. The tournament selection and the elitism are used to keep the worthy individuals in the next generation. The proposed system is applied to the one-machine infinite-bus model of a power system, and the results showed a promising possibility.

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Hierarchical Lazy Greedy Algorithm for Weapon Target Assignment (무기할당을 위한 계층적 레이지 그리디 알고리즘)

  • Jeong, Hyesun
    • Journal of the Korea Institute of Military Science and Technology
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    • v.23 no.4
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    • pp.381-388
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    • 2020
  • Weapon target assignment problem is an essential technology for automating the operator's rapid decision-making support in a battlefield situation. Weapon target assignment problem is a kind of the optimization problem that can build up an objective function by maximizing the number of threat target destructed or maximizing the survival rate of the protected assets. Weapon target assignment problem is known as the NP-Complete, and various studies have been conducted on it. Among them, a greedy heuristic algorithm which guarantees (1-1/e) approximation has been considered a very practical method in order to enhance the applicability of the real weapon system. In this paper, we formulated the weapon target assignment problem for supporting decision-making at the level of artillery. The lazy strategy based on hierarchical structure is proposed to accelerate the greedy algorithm. By experimental results, we show that our algorithm is more efficient in processing time and support the same level of the objective function value with the basic greedy algorithm.

A Study on Passive Homing Trajectory for Maximizing Target Information (표적 정보량을 최대화하는 피동 호밍궤적에 관한 고찰)

  • Ra, Won-Sang;Shin, Hyo-Sang;Jung, Bo-Young;Whang, Ick-Ho
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.68 no.1
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    • pp.172-181
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    • 2019
  • This paper deals with the problem of generating the energy optimal trajectory which is intended to enhance the target tracking performance of a passive homing missile. Noticing that the essence of passive target tracking is the range estimation problem, the target information gathered by passive measurements can be readily analyzed by introducing the range estimator designed in line-of-sight(LOS) frame. Moreover, for the linear filter structure of the suggested range estimator, the cost function associated with the target information is clearly expressed as a function of the line-of-sight rate. Based on this idea, the optimal missile trajectory maximizing the target information is obtained by solving the saddle point problem for an indefinite quadratic cost which consists of the target information and the energy. It is shown that, different from the previous heuristic approaches, the guidance command producing the optimal passive homing trajectory is produced by the modified proportional navigation guidance law whose navigation constant is determined by the weighting coefficient for target information cost.