• 제목/요약/키워드: Algorithm Model

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Vehicle trajectory prediction based on Hidden Markov Model

  • Ye, Ning;Zhang, Yingya;Wang, Ruchuan;Malekian, Reza
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권7호
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    • pp.3150-3170
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    • 2016
  • In Intelligent Transportation Systems (ITS), logistics distribution and mobile e-commerce, the real-time, accurate and reliable vehicle trajectory prediction has significant application value. Vehicle trajectory prediction can not only provide accurate location-based services, but also can monitor and predict traffic situation in advance, and then further recommend the optimal route for users. In this paper, firstly, we mine the double layers of hidden states of vehicle historical trajectories, and then determine the parameters of HMM (hidden Markov model) by historical data. Secondly, we adopt Viterbi algorithm to seek the double layers hidden states sequences corresponding to the just driven trajectory. Finally, we propose a new algorithm (DHMTP) for vehicle trajectory prediction based on the hidden Markov model of double layers hidden states, and predict the nearest neighbor unit of location information of the next k stages. The experimental results demonstrate that the prediction accuracy of the proposed algorithm is increased by 18.3% compared with TPMO algorithm and increased by 23.1% compared with Naive algorithm in aspect of predicting the next k phases' trajectories, especially when traffic flow is greater, such as this time from weekday morning to evening. Moreover, the time performance of DHMTP algorithm is also clearly improved compared with TPMO algorithm.

네트워크형 가로망의 교통신호제어 최적화 모형개발 (Development of Optimization Model for Traffic Signal Timing in Grid Networks)

  • 김영찬;유충식
    • 대한교통학회지
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    • 제18권1호
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    • pp.87-97
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    • 2000
  • Signal optimization model is divided bandwidth-maximizing model and delay-minimizing model. Bandwidth-maximizing model express model formulation as MILP(Mixed Integer Linear Programming) and delay-minimizing model like TRANSYT-7F use "hill climbing" a1gorithm to optimize signal times. This study Proposed optimization model using genetic algorithm one of evolution algorithm breaking from existing optimization model This Proposed model were tested by several scenarios and evaluated through NETSIM with TRANSYT-7F\`s outputs. The result showed capability that can obtain superior solution.

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버텍스 영역을 이용한 STL에서의 3차원 디지털 워터마킹 (A 3D Watermarking on STL using Vertex domain)

  • 김기석;천인국
    • 한국멀티미디어학회:학술대회논문집
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    • 한국멀티미디어학회 2002년도 춘계학술발표논문집(하)
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    • pp.901-906
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    • 2002
  • 본 논문은 신속조형(RP: rapid prototyping) 시스템에서 사용되며 3D 기하학적 형상 모델을 가지고 있는 STL(standard transform language)에 워터마크를 삽입하는 방법에 관한 연구이다. 제안된 알고리즘은 3D 형상 데이터의 왜곡이 전혀 없이 패싯(facet, mesh)의 버텍스(vertex) 영역에 워터마크를 삽입한다. 기존의 알고리즘으로 STL에 워터마크를 삽입할 경우, 패싯의 저장순서를 변경하는 단순한 공격으로도 워터마크가 제거된다. 제안된 알고리즘은 패싯의 저장 순서 변경과 같은 공격에 대한 강인성을 가질 뿐만 아니라, 비가시성(invisibility)도 충족한다. 제안된 알고리즘으로 STL 3D 형상에 워터마크를 삽입하고 추출하는, 실험 결과들은 3D 원형상을 전혀 왜곡하지 않고 워터마크의 삽입과 추출이 가능함을 보여준다.

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수량할인하(數量割引下)의 통합생산재고(統合生産在庫)모델에 관(關)한 연구(硏究) (A Study on the Integrated Production-Inventory Model Under Quantity Discount)

  • 한영섭;이상용
    • 품질경영학회지
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    • 제16권1호
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    • pp.78-87
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    • 1988
  • The purpose of this study is to develop the algorithm applicable to the integrated production inventory model under quantity discount. To achieve this purpose, the integrated production inventory model which unifies the inventory problem of raw materials and the finished product for a single product manufacturing system is considered. The product is manufactured in batches and the raw materials are obtained from outside suppliers but some of the raw materials are discounted according to the purchasing quantity. The intergrated production inventory problem considered in this study is formulated by the non-linear mixed integer programming model, and the optimal solution is obtained by using the algorithm developed by Goyal. Then, the algorithm developed by this study is applied to the quantity discount problem, and the optimal solution is revised by this results. The quantity discount algorithm of the integrated production inventory model developed by this study gives a systematic procedure to obtain the optimum policy to minimize the total cost in any case. The numerical example involving 20 raw materials and 5 raw materials among them are discounted according to the purchasing quantity is given to verify the mathematical model and the algorithm developed in this study.

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베이지안 기법을 활용한 공용성 모델개발 연구 (Pavement Performance Model Development Using Bayesian Algorithm)

  • 문성호
    • 한국도로학회논문집
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    • 제18권1호
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    • pp.91-97
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    • 2016
  • PURPOSES : The objective of this paper is to develop a pavement performance model based on the Bayesian algorithm, and compare the measured and predicted performance data. METHODS : In this paper, several pavement types such as SMA (stone mastic asphalt), PSMA (polymer-modified stone mastic asphalt), PMA (polymer-modified asphalt), SBS (styrene-butadiene-styrene) modified asphalt, and DGA (dense-graded asphalt) are modeled in terms of the performance evaluation of pavement structures, using the Bayesian algorithm. RESULTS : From case studies related to the performance model development, the statistical parameters of the mean value and standard deviation can be obtained through the Bayesian algorithm, using the initial performance data of two different pavement cases. Furthermore, an accurate performance model can be developed, based on the comparison between the measured and predicted performance data. CONCLUSIONS : Based on the results of the case studies, it is concluded that the determined coefficients of the nonlinear performance models can be used to accurately predict the long-term performance behaviors of DGA and modified asphalt concrete pavements. In addition, the developed models were evaluated through comparison studies between the initial measurement and prediction data, as well as between the final measurement and prediction data. In the model development, the initial measured data were used.

GA-Hard 문제를 풀기 위한 공진화 모델 (Co-Evolutionary Model for Solving the GA-Hard Problems)

  • 이동욱;심귀보
    • 한국지능시스템학회논문지
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    • 제15권3호
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    • pp.375-381
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    • 2005
  • 일반적으로 유전자 알고리즘은 최적 시스템을 디자인하는데 주로 이용된다. 하지만 알고리즘의 성능은 적합도 함수나 시스템 환경에 의해 결정된다. 두 개의 개체군이 꾸준히 상호작용하고 공진화 하는 공진화 알고리즘은 이러한 문제를 극복할 수 있을 것으로 기대된다. 본 논문에서는 GA가 풀기 어려운 GA-hard problem을 풀기 위하여 저자가 제안한 3가지 공진화 모델을 설명한다. 첫 번째 모델은 찾고자하는 해와 환경을 각각 경쟁하는 개체군으로 구성해 진화하는 방법으로 사용자의 환경설정에 의해 지역적 해를 찾는 것을 방지하는 경쟁적 공진화 알고리즘이다. 두 번째 모델은 호스트 개체군과 기생(스키마) 개체군으로 구성된 스키마 공진화 알고리즘이다. 이 알고리즘에서 스키마 개체군은 호스트 개체군에 좋은 스키마를 공급한다. 세 번째 알고리즘은 두 개체군이 서로 게임을 통해 진화하도록 하는 게임이론에 기반한 공진화 알고리즘이다. 각 알고리즘은 비주얼 서보잉, 로봇 주행, 다목적 최적화 문제에 적용하여 그 유효성을 입증한다.

다중이동물체 추적을 위한 모델생성 알고리즘 (Model Creation Algorithm for Multiple Moving Objects Tracking)

  • 조남형;김하식;이명길;이주신
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2001년도 춘계종합학술대회
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    • pp.633-637
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    • 2001
  • 본 논문은 모델기반 다중이동물체 추적을 위한 모델생성 알고리즘을 제안하였다. 제안한 알고리즘은 배경영상에 이동물체가 초기 진입했을 때의 초기모델생성 단계와 이동물체 추적 단계에서의 모델 갱신 단계로 구분하였다. 초기모델생성 단계에서는 차영상과 클러스터링 기법을 이용하여 분할된 분할영상과 현재프레임 영상에 대한 윤곽선 영상과의 로직 AND 연산을 수행하여 초기모델을 생성하였다. 모델갱신 단계에서는 하우스돌프 거리(Hausdorff Distance)와 2D-Logarithmic 탐색 알고리즘을 이용하여 추적중인 이동물체의 형태변화에 적응할 수 있도록 매 프레임 마다 새로운 모델을 갱신하였다. 실험은 도로에서 주행하는 자동차를 대상으로 도_의 실험을 수행하였다. 그 결과 도로에서 주행하는 자동차의 진입방향과 추적 대상 수가 불규칙한 경우에도 모델생성이 98% 이상 이루어짐을 알 수 있었다.

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헬리콥터의 비행영역제한 알고리즘 설계 (Design of Envelope Protection Algorithm for Helicopters)

  • 고준수;박성수;김경목
    • 한국항공운항학회지
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    • 제23권2호
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    • pp.63-68
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    • 2015
  • This paper presents the algorithm for envelope protection of helicopters. The algorithm consists of two feedback control loops: inner loop and outer loop. As an inner loop control, model following control is designed to meet the ADS-33 handling qualities specification by minimizing the tracking errors between the responses of the actual model and those of the command filter. In order to implement envelope protection, saturation limiter is imposed to command channels in command filter, whose limits are computed corresponding to the envelope limit. Fast model predictive control is designed as an outer loop control to deal with saturation constraints generated by the inner loop envelope protection and also imposed by outer loop envelope protection variables. Simulation results show that the proposed algorithm yields good envelope protection performance.

유전자 알고리즘을 이용한 Piled Raft 기초의 최적설계(II) - 실내모형실험결과의 비교 - (Optimum Design of Piled Raft Foundations Using Genetic Algorithm(II) - Comparison with Laboratory Model Test Results -)

  • 김홍택;강인규;박순규;박정주
    • 한국지반공학회:학술대회논문집
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    • 한국지반공학회 2001년도 봄 학술발표회 논문집
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    • pp.379-386
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    • 2001
  • Piled raft foundations are usually used to reduce total and differential settlements of superstructures. In the piled raft foundations, the raft is often on its own able to provide adequate bearing capacity and only few widely spaced piles are added to the foundation to keep settlements be1ow a certain limit. In this paper, experimental studies on the load sharing ratio between piles and raft are carried out. Also, for evaluating the application of optimum design technique using a genetic algorithm, optimal locations of files are compared with the results of laboratory model tests. from tile results of laboratory model tests, there are found that the load sharing ratio between files and raft is depended on the number of piles and stiffness of raft, and the optimal locations of piles became concentrated on the middle of rafts. From these results of laboratory model tests, the optimum technique using a genetic algorithm is acknowledged to the application in the piled raft.

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기동 표적 추적을 위한 유전 알고리즘 기반 상호 작용 다중 모델 기법 (GA-Based IMM Method for Tracking a Maneuvering Target)

  • 이범직;주영훈;박진배
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2002년도 하계학술대회 논문집 D
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    • pp.2382-2384
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    • 2002
  • The accuracy in maneuvering target tracking using multiple models is caused by the suitability of each target motion model to be used. The interacting multiple model (IMM) algorithm and the adaptive IMM (AIMM) algorithm require the predefined sub-models and the predetermined acceleration intervals, respectively, in consideration of the properties of maneuvers in order to construct multiple models. In this paper, to solve these problems intelligently, a genetic algorithm (GA) based-IMM method using fuzzy logic is proposed. In the proposed method, the acceleration input is regarded as an additive noise and a sub-model is represented as a set of fuzzy rules to model the time-varying variances of the process noises of a new piecewise constant white acceleration model. The proposed method is compared with the AIMM algorithm in simulations.

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