• Title/Summary/Keyword: optimal algorithm

Search Result 6,798, Processing Time 0.036 seconds

A Polynomial Time Approximation Scheme for Enormous Euclidean Minimum Spanning Tree Problem (대형 유클리드 최소신장트리 문제해결을 위한 다항시간 근사 법)

  • Kim, In-Bum
    • Journal of the Institute of Electronics Engineers of Korea CI
    • /
    • v.48 no.5
    • /
    • pp.64-73
    • /
    • 2011
  • The problem of Euclidean minimum spanning tree (EMST) is to connect given nodes in a plane with minimum cost. There are many algorithms for the polynomial time problem as EMST. However, for numerous nodes, the algorithms consume an enormous amount of time to find an optimal solution. In this paper, an approximation scheme using a polynomial time approximation scheme (PTAS) algorithm with dividing and parallel processing for the problem is suggested. This scheme enables to construct a large, approximate EMST within a short duration. Although initially devised for the non-polynomial problem, we employ naive PTAS to construct a vast EMST with dynamic programming. In an experiment, the approximate EMST constructed by the proposed scheme with 15,000 input terminal nodes and 16 partition cells shows 89% and 99% saving in execution time for the serial processing and parallel processing methods, respectively. Therefore, our scheme can be applied to obtain an approximate EMST quickly for numerous input terminal nodes.

A Study on Active Priority Control Strategy for Traffic Signal Progression of Tram (트램의 연속통행을 위한 능동식 우선신호 전략 연구)

  • Lee, In-Kyu;Kim, Young-Chan
    • The Journal of The Korea Institute of Intelligent Transport Systems
    • /
    • v.13 no.3
    • /
    • pp.25-37
    • /
    • 2014
  • Recently, our local governments are conducting the introduction of tram system because it is recognized as an effective public transit that can solve a traffic jam in downtown, decreasing public transit share and environmental issues in world wide cities. We developed the Active Priority Control Strategy to efficiently operate a tram in our existing traffic signal system. This study organized the tram system for operating the Active Priority Signal Control, developed the algorithm that calculates a tram-stop dwell time in order to pass the downstream intersection without a stop. The dwell time is determined by arrival time at tram-stop, downstream signal time, and the location of a opposite tram, it can be reduced by choosing the optimal one among Signal Priority Controls. Using the VISSIM and VISVAP model, we conducted a simulation test for the city of Chang-won that it is expected to install a tram system. It showed that a developed signal control strategy is effective to prevent a tram's stop in intersections, to reduce a tram's travel time.

Self Organizing RBF Neural Network Equalizer (자력(自力) RBF 신경망 등화기)

  • Kim, Jeong-Su;Jeong, Jeong-Hwa
    • Journal of the Institute of Electronics Engineers of Korea CI
    • /
    • v.39 no.1
    • /
    • pp.35-47
    • /
    • 2002
  • This paper proposes a self organizing RBF neural network equalizer for the equalization of digital communications. It is the most important for the equalizer using the RBF neural network to estimate the RBF centers correctly and quickly, which are the desired channel states. However, the previous RBF equalizers are not used in the actual communication system because of some drawbacks that the number of channel states has to be known in advance and many centers are necessary. Self organizing neural network equalizer proposed in this paper can implement the equalization without prior information regarding the number of channel states because it selects RBF centers among the signals that are transmitted to the equalizer by the new addition and removal criteria. Furthermore, the proposed equalizer has a merit that is able to make a equalization with fewer centers than those of prior one by the course of the training using LMS and clustering algorithm. In the linear, nonlinear and standard telephone channel, the proposed equalizer is compared with the optimal Bayesian equalizer for the BER performance, the symbol decision boundary and the number of centers. As a result of the comparison, we can confirm that the proposed equalizer has almost similar performance with the Bavesian enualizer.

A Study on the FSK Synchronization and MODEM Techniques for Mobile Communication Part II : Performance Analysis and Design of The FSK MODEM (이동통신을 위한 FSK 동기 및 변복조기술에 관한 연구 II부. FSK 모뎀 설계 및 성능평가)

  • Kim, Gi-Yun;Choe, Hyeong-Jin;Jo, Byeong-Hak
    • Journal of the Institute of Electronics Engineers of Korea TC
    • /
    • v.37 no.3
    • /
    • pp.9-17
    • /
    • 2000
  • In this paper we implement computer simulation system of 4FSK signal MODEM using Quadrature detector and analyze overall tranceiver system. We follow the FLEX wireless paging system standards and construct premodulation filter and data frame. We propose an efficient open loop symbol timing recovery algorithm which takes advantage of 128 bit length preamble pattern and also propose a 32 bit UW pattern which Is based on the optimal UW detection method, and excellent aperiodic autocorrelation characteristic. The BER simulation in the fading channel as well as AWGN is performed with BCH coding and Interleaving to the Quadrature detector system and it is shown that a high coding fain occurs in the fading channel rather than AWGN channel.

  • PDF

A study on the fault diagnosis of rotating machine by machine learning (기계학습을 적용한 회전체 고장진단에 관한 연구)

  • Jeon, Hang-Kyu;Kim, Ji-Sun;Kim, Bong-Ju;Kim, Won-Jin
    • The Journal of the Acoustical Society of Korea
    • /
    • v.39 no.4
    • /
    • pp.263-269
    • /
    • 2020
  • In this study, a rotating machine that can reproduce normal condition and 8 fault conditions were produced, and vibration data was acquired. Feature is calculated from the acquired data, and accuracy is analyzed through fault diagnosis using artificial neural networks and genetic algorithms. In order to achieve optimal timing and higher accuracy, features by three domains were applied to the fault diagnosis. The learning number was selected as a setting variable. As a result of the rotating machine fault diagnosis, high precision was found in the frequency domain than in others, and precise fault diagnoses were accomplished through all of 10 operations, at the learning number of 5000 and 8000. Given the efficiency of time, it was estimated to be the most efficient when the number of learning was 5000.

Development of the Preliminary Cost Estimate Method for the Free-Form Building Facade Trade in Conjunction with the Panel Optimization Algorithm Process (곡면 최적화 알고리즘을 활용한 비정형 건축물 외장공사비 개산견적에 관한 연구)

  • Lim, Jang Sik;Ock, Jong Ho
    • Korean Journal of Construction Engineering and Management
    • /
    • v.15 no.4
    • /
    • pp.95-106
    • /
    • 2014
  • The outer surfaces of free form buildings contain panels with two-directional curvatures. To construct these panels, complex geometric surfaces should be divided into forms and sizes that can be manufactured and constructed efficiently. Because the bigger the curvatures of these panel, the more expensive the construction costs, these complex curvatures should go through optimal process of reinterpretation to minimize the curved surfaces with complex two-directional curvatures, which is called panel optimization. Small construction and design companies have trouble in calculating even rough estimate and cannot adjust expected construction cost of the panels based on comparison of design alternatives in conjunction with panel optimization process due to lack of knowledge and experience. This study conducts the research that can support designers' cost decision-making in the design stage of the free form buildings with respect to the panel optimization process. A 3D commercial application specialized to modeling free form shapes is used for the purpose.

Load Balancing Scheme in Heterogeneous Multiple AS Environment based on IMS Network (IMS 네트워크 기반 이종 다중 AS 환경에서의 부하 분산 기법)

  • Yoo, Yung-Jun;Cho, Yoon-Sang;Song, Min-Do;Kim, Moo-Hyun
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.36 no.3A
    • /
    • pp.250-258
    • /
    • 2011
  • In this paper we propose a load balancing scheme for heterogeneous multiple AS's (Application Server) in IMS (IP Multimedia Subsystem) based network. In IMS network, to perform load balancing among multiple ASs with different registration pattern, different weight value should be set for each AS. In previous systems, there exists an inconvenience that the weight value should be set manually by the operator after monitoring the result. In this paper we propose a method to calculate optimal weight in automatic manner and to perform load balancing simultaneously. We also propose a simplified algorithm to reduce calculation in specific situation and present a way to apply our proposed scheme in adaptive manner according to the situation. Through simulation result, we verify that our proposing scheme outperforms previous schemes in load balancing and adjusts well to the change of the system in automatic manner with fast convergence.

Self-Organizing Fuzzy Polynomial Neural Networks by Means of IG-based Consecutive Optimization : Design and Analysis (정보 입자기반 연속전인 최적화를 통한 자기구성 퍼지 다항식 뉴럴네트워크 : 설계와 해석)

  • Park, Ho-Sung;Oh, Sung-Kwun
    • The Transactions of the Korean Institute of Electrical Engineers D
    • /
    • v.55 no.6
    • /
    • pp.264-273
    • /
    • 2006
  • In this paper, we propose a new architecture of Self-Organizing Fuzzy Polynomial Neural Networks (SOFPNN) by means of consecutive optimization and also discuss its comprehensive design methodology involving mechanisms of genetic optimization. The network is based on a structurally as well as parametrically optimized fuzzy polynomial neurons (FPNs) conducted with the aid of information granulation and genetic algorithms. In structurally identification of FPN, the design procedure applied in the construction of each layer of a SOFPNN deals with its structural optimization involving the selection of preferred nodes (or FPNs) with specific local characteristics and addresses specific aspects of parametric optimization. In addition, the fuzzy rules used in the networks exploit the notion of information granules defined over system's variables and formed through the process of information granulation. That is, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. This granulation is realized with the aid of the hard c-menas clustering method (HCM). For the parametric identification, we obtained the effective model that the axes of MFs are identified by GA to reflect characteristic of given data. Especially, the genetically dynamic search method is introduced in the identification of parameter. It helps lead to rapidly optimal convergence over a limited region or a boundary condition. To evaluate the performance of the proposed model, the model is experimented with using two time series data(gas furnace process, nonlinear system data, and NOx process data).

The Effect of the Number of Phoneme Clusters on Speech Recognition (음성 인식에서 음소 클러스터 수의 효과)

  • Lee, Chang-Young
    • The Journal of the Korea institute of electronic communication sciences
    • /
    • v.9 no.11
    • /
    • pp.1221-1226
    • /
    • 2014
  • In an effort to improve the efficiency of the speech recognition, we investigate the effect of the number of phoneme clusters. For this purpose, codebooks of varied number of phoneme clusters are prepared by modified k-means clustering algorithm. The subsequent processing is fuzzy vector quantization (FVQ) and hidden Markov model (HMM) for speech recognition test. The result shows that there are two distinct regimes. For large number of phoneme clusters, the recognition performance is roughly independent of it. For small number of phoneme clusters, however, the recognition error rate increases nonlinearly as it is decreased. From numerical calculation, it is found that this nonlinear regime might be modeled by a power law function. The result also shows that about 166 phoneme clusters would be the optimal number for recognition of 300 isolated words. This amounts to roughly 3 variations per phoneme.

A Study on Unmanned Vehicles Estimation using Steepest Descent, Wiener and Bartlett Algorithm (최급 하강법 및 위너 방법을 Bartlett알고리즘에 적용한 무인 이동체 탐지 방법에 대한 연구)

  • Lee, Kwan-Hyeong;Song, Woo-Young
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
    • /
    • v.10 no.2
    • /
    • pp.154-160
    • /
    • 2017
  • In this paper, we studied the Bartlett method to correctly estimate the targets of a unmanned vehicles. The Bartlett method estimates the desired signals by making the gain constant for the received signal incident on the array antenna. In this paper, the weights of the Bartlett method are updated by applying the winner method and steepest descent method in order to estimation the accurate unmanned. The updated weights improve the resolution of the existing Bartlett method by applying optimal weights to all received signals received at the array antenna. Through simulation, we are comparative analysis about the performance of proposed method. From result of simulation, We showed the superior performance of the proposed method relative to the classical method, and Bartlett using steep descent method showed more superior than one using wiener method.