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Low Power Module selection using Genetic Algorithm (유전자 알고리듬을 사용한 저전력 모듈 선택)

  • Jeon, Jong-Sik
    • The Journal of the Korea institute of electronic communication sciences
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    • v.2 no.3
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    • pp.174-179
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    • 2007
  • In this paper, we present a optimal module selection using genetic algorithm under the power, area, delay constraint. The proposed algorithm use the way of optimal module selection it will be able to minimize power consumption. In the comparison and experimental results, The proposed application algorithm reduce maximum power saving up to 26.9% comparing to previous non application algorithm, and reduce minimum power saving up to 9.0%. It also show the average power saving up to 15.525% and proved the power saving efficiency.

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Optimal Capacitor Placement Considering Voltage-stability Margin with Hybrid Particle Swarm Optimization

  • Kim, Tae-Gyun;Lee, Byong-Jun;Song, Hwa-Chang
    • Journal of Electrical Engineering and Technology
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    • v.6 no.6
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    • pp.786-792
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    • 2011
  • The present paper presents an optimal capacitor placement (OCP) algorithm for voltagestability enhancement. The OCP issue is represented using a mixed-integer problem and a highly nonlinear problem. The hybrid particle swarm optimization (HPSO) algorithm is proposed to solve the OCP problem. The HPSO algorithm combines the optimal power flow (OPF) with the primal-dual interior-point method (PDIPM) and ordinary PSO. It takes advantage of the global search ability of PSO and the very fast simulation running time of the OPF algorithm with PDIPM. In addition, OPF gives intelligence to PSO through the information provided by the dual variable of the OPF. Numerical results illustrate that the HPSO algorithm can improve the accuracy and reduce the simulation running time. Test results evaluated with the three-bus, New England 39-bus, and Korea Electric Power Corporation systems show the applicability of the proposed algorithm.

A Study of Automatic Multi-Target Detection and Tracking Algorithm using Highest Probability Data Association in a Cluttered Environment (클러터가 존재하는 환경에서의 HPDA를 이용한 다중 표적 자동 탐지 및 추적 알고리듬 연구)

  • Kim, Da-Soul;Song, Taek-Lyul
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.10
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    • pp.1826-1835
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    • 2007
  • In this paper, we present a new approach for automatic detection and tracking for multiple targets. We combine a highest probability data association(HPDA) algorithm for target detection with a particle filter for multiple target tracking. The proposed approach evaluates the probabilities of one-to-one assignments of measurement-to-track and the measurement with the highest probability is selected to be target- originated, and the measurement is used for probabilistic weight update of particle filtering. The performance of the proposed algorithm for target tracking in clutter is compared with the existing clustering algorithm and the sequential monte carlo method for probability hypothesis density(SMC PHD) algorithm for multi-target detection and tracking. Computer simulation studies demonstrate that the HPDA algorithm is robust in performing automatic detection and tracking for multiple targets even though the environment is hostile in terms of high clutter density and low target detection probability.

A Branch and Bound Algorithm for Solving a Capacitated Subtree of Tree Problem in Local Access Telecommunication Networks

  • Cho, Geon;Kim, Seong-Lyun
    • Journal of the Korean Operations Research and Management Science Society
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    • v.22 no.3
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    • pp.81-98
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    • 1997
  • Given a rooted tree T with profits and node demands, the capacitated subtree of a tree problem (GSTP) consists of finding a rooted subtree of maximum profit, subject to having total demand no larger than the given capacity H. We first define the so-called critical item for CSTP and find an upper bound on the optimal value of CSTP in O(n$^{2}$) time, where n is the number of nodes in T. We then present our branch and bound algorithm for solving CSTP and illustrate the algiruthm by using an example. Finally, we implement our branch-and-bound algorithm and compare the computational results with those for both CPLEX and a dynamic programming algorithm. The comparison shows that our branch-and-bound algorithm performs much better than both CPLEX and the dynamic programming algorithm, where n and H are the range of [50, 500] and [5000, 10000], respectively.

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Search Method for Consensus Pattern of Transcription Factor Binding Sites in Promoter Region (프로모터 영역의 전사인자 결합부위 Consensus 패턴 탐색 방법)

  • Kim, Ki-Bong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.9 no.5
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    • pp.1218-1224
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    • 2008
  • Located on the upstream of a gene, the promoter region that plays a very important role in the control of gene expression as a signal part has various binding sites for transcription factors. These binding sites are present in various parts of the promoter region and assume an aspect of highly conserved consensus sequence pattern. This paper deals with the introductions of search methods for consensus pattern, including Wataru method, EM algorithm, MEME algorithm, Genetic algorithm and Phylogenetic Footprinting method, and intends to give future prospects of research on this field.

Application of Parameters-Free Adaptive Clonal Selection in Optimization of Construction Site Utilization Planning

  • Wang, Xi;Deshpande, Abhijeet S.;Dadi, Gabriel B.
    • Journal of Construction Engineering and Project Management
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    • v.7 no.2
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    • pp.1-10
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    • 2017
  • The Clonal Selection Algorithm (CSA) is an algorithm inspired by the human immune system mechanism. In CSA, several parameters needs to be optimized by large amount of sensitivity analysis for the optimal results. They limit the accuracy of the results due to the uncertainty and subjectivity. Adaptive Clonal Selection (ACS), a modified version of CSA, is developed as an algorithm without controls by pre-defined parameters in terms of selection process and mutation strength. In this paper, we discuss the ACS in detail and present its implementation in construction site utilization planning (CSUP). When applied to a developed model published in research literature, it proves that the ACS are capable of searching the optimal layout of temporary facilities on construction site based on the result of objective function, especially when the parameterization process is considered. Although the ACS still needs some improvements, obtaining a promising result when working on a same case study computed by Genetic Algorithm and Electimze algorithm prove its potential in solving more complex construction optimization problems in the future.

New Power Flow Calculation Using Improved Genetic Algorithm (개선된 유전 알고리즘을 이용한 새로운 전력조류계산)

  • Chae, Myung-Suck;Lee, Tae-Hyung;Shin, Joong-Rin;Im, Han-Seok
    • Proceedings of the KIEE Conference
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    • 1999.11a
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    • pp.43-51
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    • 1999
  • The power flow calculations(PFc) are the most important and powerful tools in power systems engineering. The conventional power flow problem is solved generally with numerical methods such as Newton-Raphson(NR). The conventional numerical method generally have some convergency problem, which is sensitive to initial value, and numerical stability problem concerned with jacobian matrix inversion. This paper presents a new PFc algorithm based on the improved genetic algorithm (IGA) which can overcome the disadvantages mentioned above. The parameters of GA, with dynamical hierarchy of the coding system, are improved to make GA a practical algorithm in the problem of real system. Some case studies with test bus system also present to show the performance of proposed algorithm. The results of proposed algorithm are compared with the results of PFc obtained using a conventional NR method.

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Analysis of Criteria for Selecting Load Redistribution Algorithm for Fault-Tolerant Distributed System (분산 시스템의 결함시 재분배 알고리즘의 선정기준을 위한 특성 분석)

  • 최병갑
    • Journal of the Korea Society for Simulation
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    • v.3 no.1
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    • pp.89-98
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    • 1994
  • In this paper, a criteria for selecting an appropriate load redistribution algorithm is devised so that a fault-tolerance distributed system can operte at its optimal efficience. To present the guideline for selecting redistributing algorithms, simulation models of fault-tolerant system including redistribution algorithms are developed using SLAM II. The job arrival rate, service rate, failure and repair rate of nodes, and communication delay time due to load migration are used as parameters of simulation. The result of simulation shows that the job arrival rate and the failure rate of nodes are not deciding factors in affecting the relative efficiency of algorithms. Algorithm B shows relatively a consistent performance under various environments, although its performance is between those of other algorithms. If the communication delay time is longer than average job processing time, the performance of algorithm B is better than others. If the repair rate is relatively small or communication delay time is longer than service time, algorithm A leads to good performance. But in opposite environments, algorithm C is superior to other algorithms.

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Improvement of Recognition Performance for Limabeam Algorithm by using MLLR Adaptation

  • Nguyen, Dinh Cuong;Choi, Suk-Nam;Chung, Hyun-Yeol
    • IEMEK Journal of Embedded Systems and Applications
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    • v.8 no.4
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    • pp.219-225
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    • 2013
  • This paper presents a method using Maximum-Likelihood Linear Regression (MLLR) adaptation to improve recognition performance of Limabeam algorithm for speech recognition using microphone array. From our investigation on Limabeam algorithm, we can see that the performance of filtering optimization depends strongly on the supporting optimal state sequence and this sequence is created by using Viterbi algorithm trained with HMM model. So we propose an approach using MLLR adaptation for the recognition of speech uttered in a new environment to obtain better optimal state sequence that support for the filtering parameters' optimal step. Experimental results show that the system embedded with MLLR adaptation presents the word correct recognition rate 2% higher than that of original calibrate Limabeam and also present 7% higher than that of Delay and Sum algorithm. The best recognition accuracy of 89.4% is obtained when we use 4 microphones with 5 utterances for adaptation.

A Visual Inspection System for Gravure Printing Using Perimetric Mask and Symmetry Transform Algorithm (주변마스크와 대칭변환 알고리즘을 이용한 그라비아 인쇄 불량 검사시스템)

  • 이칠우;김만진;기명석
    • Journal of Institute of Control, Robotics and Systems
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    • v.9 no.12
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    • pp.984-993
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    • 2003
  • In Gravure printing process, there are a lot of printing errors caused by expansion and contraction of printing materials and difficulty of printing of small letters, accordingly we cannot detect those errors with eyes. In this paper, we describe the algorithm which can detect small errors automatically in Gravure printing process and a real-time detection system adopting the algorithm. We present the Perimetric Mask algorithm that can eliminate tiny errors occurring near the contour of printing objects to achieve accurate inspection, and also construct an algorithm utilizing symmetry transform which can emphasize tiny errors to make a robust inspection system. We have made a system running in real-time and verified the efficiency of the algorithm.