• 제목/요약/키워드: Data Optimization

검색결과 3,509건 처리시간 0.032초

MIL-STD-1553B 통신에서 샘플링 기반 최적화 기법을 이용한 효율적 임무 자료 전송 (Efficient Mission Data Transmission with Sampling-Based Optimization in MIL-STD-1553B)

  • 이헌철;김기표;권용성
    • 한국군사과학기술학회지
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    • 제21권3호
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    • pp.370-378
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    • 2018
  • The mission data in missile systems should be quickly and reliably transmitted from a mission transmission device to a guidance control unit. The MIL-STD-1553B is one of the reliable communication standards, but its bit rate is generally limited to 1Mbps due to the intrinsic properties of its electrical design. Therefore, the bus controller needs to be optimized to efficiently transmit the mission data on the inevitably limited bit rate. This paper proposes an analytical approach based on sampling-based optimization methods to maximize the data throughput without data loss. The proposed approach was evaluated in the simulations with the data transmission model for the MIL-STD-1553B communication system. The results of the proposed methods were applied to a real-time system and showed that the proposed method was successfully performed.

Analysis and Compression of Spun-yarn Density Profiles using Adaptive Wavelets

  • Kim, Joo-Yong
    • 한국염색가공학회지
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    • 제18권5호
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    • pp.88-93
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    • 2006
  • A data compression system has been developed by combining adaptive wavelets and optimization technique. The adaptive wavelets were made by optimizing the coefficients of the wavelet matrix. The optimization procedure has been performed by criteria of minimizing the reconstruction error. The resulting adaptive basis outperformed such conventional basis as Daubechies-5 by 5-10%. It was also shown that the yarn density profiles could be compressed by over 95% without a significant loss of information.

Loss Function Approach to Multiresponse Robust Design

  • Chang, Duk-Joon;Kwon, Yong-Man
    • Journal of the Korean Data and Information Science Society
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    • 제16권2호
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    • pp.255-261
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    • 2005
  • Many designed experiments require the simultaneous optimization of multiple responses. In this paper, we propose how to simultaneously optimize multiple responses for robust design when data are collected from a combined array. The proposed method is based on the quadratic loss function. An example is illustrated to show the proposed method.

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다분야 통합환경에서의 데이터베이스 설계 연구 (A Study on the Database Design in the MDO Environment)

  • 황진용;정주영;이재우;변영환
    • 한국항공우주학회지
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    • 제31권5호
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    • pp.25-36
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    • 2003
  • 항공기 설계는 설계 전 분야에 걸친 설계 요소들을 모두 고려한 통합적 환경에서 이루어 져야 한다. 이를 위해 각 분야간의 데이터 공유 및 일관성, 무결성, 최신성 등이 요구되며 이러한 요구사항을 만족할 수 있는 효율적인 데이터베이스의 설계가 필요하다. 데이터베이스의 설계 순기는 저장되고 관리해야 할 데이터의 분석, E-R Diagram의 작성, 테이블 사상으로 이루어진다. 본 연구에서는 상용의 Oracle 8i 데이터베이스 관리시스템을 이용하여 데이터베이스를 설계, 구축하였다. MDF(MultiDisplinary Feasible), IDF(Individual Discipline Feasible), CO(Collaborative Optimization) 등의 MDO(Multidisciplinary Design Optimization) 기법을 적용할 수 있는 데이터베이스의 설계과정을 정립하고, 간단한 수치예제와 무인전투기 최적화 설계 등의 예제를 통하여 통합환경에서의 데이터베이스 설계 방법의 타당성을 검증하였다.

입자 군집 최적화법을 이용한 소형루프 전자탐사 자료의 층서구조 전기비저항 역해석 (Layered-earth Resistivity Inversion of Small-loop Electromagnetic Survey Data using Particle Swarm Optimization)

  • 장한길로
    • 지구물리와물리탐사
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    • 제22권4호
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    • pp.186-194
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    • 2019
  • 물리탐사 자료의 역산 해를 찾는데 흔히 이용되는 결정론적 해법은 지역 최소점에 빠져 적절한 해에 수렴하지 못할 가능성이 크다는 단점이 존재한다. 이 문제를 해결하기 위한 대안 중 하나는 확률론적 접근법에 기반한 전역 최적화 방법을 이용하는 것이며, 여러 방법들 중에서 입자 군집 최적화(Particle Swarm Optimization, PSO)법의 적용사례가 많이 소개되었다. 이 논문에서는 PSO법을 이용한 소형루프 전자탐사 자료의 층서 구조 전기비저항 역해석 알고리즘을 개발하고 합성자료를 이용하여 역산실험을 수행하였다. 실험결과 기존의 Gauss-Newton 알고리즘으로는 최적의 역산해를 찾는데 어려움이 있는 소형루프 전자탐사 자료의 역산 시도에 PSO 방법을 적용하면 성공률을 높일 수 있음을 확인하였다.

Data Interpolation and Design Optimisation of Brushless DC Motor Using Generalized Regression Neural Network

  • Umadevi, N.;Balaji, M.;Kamaraj, V.;Padmanaban, L. Ananda
    • Journal of Electrical Engineering and Technology
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    • 제10권1호
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    • pp.188-194
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    • 2015
  • This paper proposes a generalized regression neural network (GRNN) based algorithm for data interpolation and design optimization of brushless dc (BLDC) motor. The procedure makes use of magnet length, stator slot opening and air gap length as design variables. Cogging torque and average torque are treated as performance indices. The optimal design necessitates mitigating the cogging torque and maximizing the average torque by varying design variables. The data set for interpolation and ensuing design optimisation using GRNN is obtained by modeling a standard BLDC motor using finite element analysis (FEA) tool MagNet 7.1.1. The performance indices of the standard motor obtained using FEA are validated with an experimental model and an analytical method. The optimal design is authenticated using particle swarm optimization (PSO) algorithm and the performance indices of the optimal design obtained using GRNN is validated using FEA. The results indicate the suitability of GRNN as an interpolation and design optimization tool for a BLDC motor.

Global Optimization of Clusters in Gene Expression Data of DNA Microarrays by Deterministic Annealing

  • Lee, Kwon Moo;Chung, Tae Su;Kim, Ju Han
    • Genomics & Informatics
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    • 제1권1호
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    • pp.20-24
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    • 2003
  • The analysis of DNA microarry data is one of the most important things for functional genomics research. The matrix representation of microarray data and its successive 'optimal' incisional hyperplanes is a useful platform for developing optimization algorithms to determine the optimal partitioning of pairwise proximity matrix representing completely connected and weighted graph. We developed Deterministic Annealing (DA) approach to determine the successive optimal binary partitioning. DA algorithm demonstrated good performance with the ability to find the 'globally optimal' binary partitions. In addition, the objects that have not been clustered at small non­zero temperature, are considered to be very sensitive to even small randomness, and can be used to estimate the reliability of the clustering.

Multi-Objective Design Exploration and its Applications

  • Obayashi, Shigeru;Jeong, Shin-Kyu;Shimoyama, Koji;Chiba, Kazuhisa;Morino, Hiroyuki
    • International Journal of Aeronautical and Space Sciences
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    • 제11권4호
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    • pp.247-265
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    • 2010
  • Multi-objective design exploration (MODE) and its applications are reviewed as an attempt to utilize numerical simulation in aerospace engineering design. MODE reveals the structure of the design space based on trade-off information. A self-organizing map (SOM) is incorporated into MODE as a visual data mining tool for the design space. SOM divides the design space into clusters with specific design features. This article reviews existing visual data mining techniques applied to engineering problems. Then, we discuss three applications of MODE: multidisciplinary design optimization for a regional-jet wing, silent supersonic technology demonstrator and centrifugal diffusers.

다중사용자 OFDM 광대역 무선인터넷 시스템의 자원할당 방법 (Resouce Allocation for Multiuser OFDM Systems)

  • 정용주;백천현;김후곤
    • 한국경영과학회지
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    • 제32권3호
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    • pp.33-46
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    • 2007
  • This study deals with the adaptive multiuser OFDM (Orthogonal Frequency Division Multiplexing) system which adjusts the resource allocation according to the environmental changes in such as wireless and quality of service required by users. The resource allocation includes subcarrier assignment to users, modulation method and power used for subcarriers. We first develop a general optimization model which maximizes data throughput while satisfying data rates required by users and total power constraints. Based on the property that this problem has the 0 duality gap, we apply the subgradient dual optimization method which obtains the solution of the dual problem by iteration of simple calculations. Extensive experiments with realistic data have shown that the subgradient dual method is applicable to the real world system, and can be used as a dynamic resource allocation mechanism.

인공지능을 이용한 휴머노이드 로봇의 자세 최적화 (Optimization of Posture for Humanoid Robot Using Artificial Intelligence)

  • 최국진
    • 한국산업융합학회 논문집
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    • 제22권2호
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    • pp.87-93
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    • 2019
  • This research deals with posture optimization for humanoid robot against external forces using genetic algorithm and neural network. When the robot takes a motion to push an object, the torque of each joint is generated by reaction force at the palm. This study aims to optimize the posture of the humanoid robot that will change this torque. This study finds an optimized posture using a genetic algorithm such that torques are evenly distributed over the all joints. Then, a number of different optimized postures are generated from various the reaction forces at the palm. The data is to be used as training data of MLP(Multi-Layer Perceptron) neural network with BP(Back Propagation) learning algorithm. Humanoid robot can find the optimal posture at different reaction forces in real time using the trained neural network include non-training data.