• Title/Summary/Keyword: Multi-step prediction

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Multi-step Ahead Link Travel Time Prediction using Data Fusion (데이터융합기술을 활용한 다주기 통행시간예측에 관한 연구)

  • Lee, Young-Ihn;Kim, Sung-Hyun;Yoon, Ji-Hyeon
    • Journal of Korean Society of Transportation
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    • v.23 no.4 s.82
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    • pp.71-79
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    • 2005
  • Existing arterial link travel time estimation methods relying on either aggregate point-based or individual section-based traffic data have their inherent limitations. This paper demonstrates the utility of data fusion for improving arterial link travel time estimation. If the data describe traffic conditions, an operator wants to know whether the situations are going better or worse. In addition, some traffic information providing strategies require predictions of what would be the values of traffic variables during the next time period. In such situations, it is necessary to use a prediction algorithm in order to extract the average trends in traffic data or make short-term predictions of the control variables. In this research. a multi-step ahead prediction algorithm using Data fusion was developed to predict a link travel time. The algorithm performance were tested in terms of performance measures such as MAE (Mean Absolute Error), MARE(mean absolute relative error), RMSE (Root Mean Square Error), EC(equality coefficient). The performance of the proposed algorithm was superior to the current one-step ahead prediction algorithm.

Closed-loop predictive control using periodic gain

  • Lee, Young-Il
    • 제어로봇시스템학회:학술대회논문집
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    • 1994.10a
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    • pp.173-176
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    • 1994
  • In this paper a closed-form predictive control which takes the intervalwise receding horizon strategy is presented and its stability properties are investigated. A slate-space form output predictor is derived which is composed of the one-step ahead optimal output prediction, input and output data of the system. A set of feedback gains are obtained using the dynamic programming algorithm so that they minimize a multi-stage quadratic cost function and they are used periodically.

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Development of Thermal Performance Prediction for Large Planar Military Antenna with Multi-Cooling Channels (다중 냉각유로가 적용된 수랭식 군사용 대면적 안테나의 열성능 예측 기술)

  • YeRyun Lee;SungWook Jang;PilGyeong Choi;NohJin Kwak;JunJung Park
    • Journal of the Korea Institute of Military Science and Technology
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    • v.27 no.1
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    • pp.43-50
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    • 2024
  • Large planar military antenna boasts a range of electrical components, including TRA(Transmit-Receive Assembly), signal processors, etc. which engage in computations and calculations. These processes generate a significant amount of heat, leading to unforeseen consequences for the equipment. To mitigate these adverse effects, it's imperative to implement a cooling system that can effectively reduce heat-related issues. Given the antenna's intricate nature and the multitude of components it houses, a two-step estimation process is necessary. The first step involves a comprehensive model calculation to determine the total flow characteristics, while the second step entails a thermal analysis of individual TRA set. In this study, we depicted an antenna set using simplified 3D models of its components, considering their material and thermal properties. The sequential analysis process facilitated the calculation of branched flow rates, providing insights into the individual TRA. This approach also allowed us to design a cooling system for the TRA set, assessing its thermal stability in high-temperature environments. To ensure the optimal performance of TRA, breaking down the analysis into stages based on the cooling system's structure can assist operators in predicting numerical results more effectively.

Study on abnormal behavior prediction models using flexible multi-level regression (유연성 다중 회귀 모델을 활용한 보행자 이상 행동 예측 모델 연구)

  • Jung, Yu Jin;Yoon, Yong Ik
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.1
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    • pp.1-8
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    • 2016
  • In the recently, violent crime and accidental crime has been generated continuously. Consequently, people anxiety has been heightened. The Closed Circuit Television (CCTV) has been used to ensure the security and evidence for the crimes. However, the video captured from CCTV has being used in the post-processing to apply to the evidence. In this paper, we propose a flexible multi-level models for estimating whether dangerous behavior and the environment and context for pedestrians. The situation analysis builds the knowledge for the pedestrians tracking. Finally, the decision step decides and notifies the threat situation when the behavior observed object is determined to abnormal behavior. Thereby, tracking the behavior of objects in a multi-region, it can be seen that the risk of the object behavior. It can be predicted by the behavior prediction of crime.

Position Control of Linear Motor-based Container Transfer System using DR-FNNs (DR-FNNs를 이용한 리니어 모터 기반 컨테이너 이송시스템의 위치제어)

  • Lee, Jin-Woo;Suh, Jin-Ho;Lee, Young-Jin;Lee, Kwan-Soon
    • Journal of Navigation and Port Research
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    • v.28 no.6
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    • pp.541-548
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    • 2004
  • In the maritime container terminal. LMCTS (Linear Motor-based Container Transfer System) is horizontal transfer system for the yard automation, which In., been proposed to take the place of AGV (Automated Guided Vehicle). The system is based on PMLSM (Permanent Magnetic Linear Synchronous Motor) that is consists of stator modules on the rail and shuttle car (mover). Because of large variant of mover's weight by loading and unloading containers, the difference of each characteristic of stator modules, and a stator module's trouble etc. LMCTS is considered as that the system is changed its model suddenly and variously. In this paper, we will introduce the softcomputing method of a multi-step prediction control for LMCTS using DR- FNN (Dynamically-constructed Recurrent Fuzzy Neural Network). The proposed control system is used two networks for multi step prediction Consequently, the system has an ability to adapt for external disturbance, detent force, force ripple, and sudden changes by loading and unloading the container.

Improved DMC for the integrating process (적분 공정 제어를 위한 향상된 DMC)

  • 강병삼;한종훈;장근수
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.1120-1123
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    • 1996
  • DMC(Dynamic Matrix Control) algorithm has been successfully used in industries for more than a decade. It can handle constraints and easily extended to MIMO case. The application of DMC, however, is limited to the open loop stable process because it uses the FIR(Finite Impulse Response) or FSR(Finite Step Response) model. Integrating process widely used in chemical process industry, is the representative open loop unstable process. The disturbance rejection of DMC is relatively poor due to the assumption that the current disturbance is equivalent to the future disturbance. We propose the IDMC(Improved Dynamic Matrix Control) for the integrating process, as well as non-integrating process. IDMC has shown better disturbance rejection using multi-step ahead predictor for the disturbance.

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A development of multi-step neural network predictive controller (다단 신경회로망 예측제어기 개발)

  • 이권순
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.35C no.8
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    • pp.68-74
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    • 1998
  • The neural network predictiv econtroller (NNPC) is proposed for the attempt to mimic the function of brain that forecasts the future. It consists of two loops, one is for the prediction of output (NNP:neural network predictor) and the other one is for control the plant(NNC: neural network controller). The output of NNC makes the control input of plant, which is followed by the variation of both plant error and predictin error. The NNP forecasts the future output based upon the current control input and the estimated control output. The input and the output data of a system and a new method using evolution strategy are used to train the NNP. A two-step NNPC is applied to control the temeprature in boiler systems. It was compared with PI controller and auto-tuning PID controller. The computer simulaton and experimental results show that the proposed method has better performances than the other method.

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Fuzzy Neural Network Based Generalized Predictive Control of Chaotic Nonlinear Systems (혼돈 비선형 시스템의 퍼지 신경 회로망 기반 일반형 예측 제어)

  • Park, Jong-Tae;Park, Yoon-Ho
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.53 no.2
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    • pp.65-75
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    • 2004
  • This paper presents a generalized predictive control method based on a fuzzy neural network(FNN) model, which uses the on-line multi-step prediction, fur the intelligent control of chaotic nonlinear systems whose mathematical models are unknown. In our design method, the parameters of both predictor and controller are tuned by a simple gradient descent scheme, and the weight parameters of FNN are determined adaptively during the operation of the system. In order to design a generalized predictive controller effectively, this paper describes computing procedure for each of the two important parameters. Also, we introduce a projection matrix to determine the control input, which deceases the control performance function very rapidly. Finally, in order to evaluate the performance of our controller, the proposed method is applied to the Doffing and Henon systems, which are two representative continuous-time and discrete-time chaotic nonlinear systems, res reactively.

Polyethylene flow prediction with a differential multi-mode Pom-Pom model

  • Rutgers, R.P.G.;Clemeur, N.;Debbaut, B.
    • Korea-Australia Rheology Journal
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    • v.14 no.1
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    • pp.25-32
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    • 2002
  • We report the first steps of a collaborative project between the University of Queensland, Polyflow, Michelin, SK Chemicals, and RMIT University, on simulation, validation and application of a recently introduced constitutive model designed to describe branched polymers. Whereas much progress has been made on predicting the complex flow behaviour of many - in particular linear - polymers, it sometimes appears difficult to predict simultaneously shear thinning and extensional strain hardening behaviour using traditional constitutive models. Recently a new viscoelastic model based on molecular topology, was proposed by McLeish and carson (1998). We explore the predictive power of a differential multi-mode version of the porn-pom model for the flow behaviour of two commercial polymer melts: a (long-chain branched) low-density polyethylene (LDPE) and a (linear) high-density polyethylene (HDPE). The model responses are compared to elongational recovery experiments published by Langouche and Debbaut (19c99), and start-up of simple shear flow, stress relaxation after simple and reverse step strain experiments carried out in our laboratory.

Impeller Redesign of Multi-stage Centrifugal Pumps (다단 원심펌프 임펠러의 개량 수력설계)

  • Oh, JongSik;Kim, DongSoo
    • 유체기계공업학회:학술대회논문집
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    • 2001.11a
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    • pp.177-184
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    • 2001
  • For two kinds of the multi-stage centrifugal pump with diffuser vanes and return channel vanes the meanline performance prediction is applied to get information of hydraulic performance at each internal flow station, because only flange-to-flange test curves are available. As a first step of redesign fur higher efficiency, the impeller geometry is numerically investigated in the present study. Quasi-3D inviscid loading distributions are obtained, for the two impellers, using the state-of-the-art method of impeller 3D design, which provides a guide to optimal redesign. Full 3D turbulent flow fields are thereafter analyzed, using the specialized CFD code, to confirm the redesign results. The inherent limitation of the traditional graphic method of impeller design, which most of domestic pump manufacturers are now employing, is found.

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