• Title/Summary/Keyword: Output Prediction

검색결과 731건 처리시간 0.029초

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

  • 이권순
    • 전자공학회논문지C
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    • 제35C권8호
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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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소수력발전소의 출력특성 분석 (Output Characteristic Analysis of Small Hydropower Plant)

  • 박완순;이철형
    • 한국신재생에너지학회:학술대회논문집
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    • 한국신재생에너지학회 2006년도 춘계학술대회
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    • pp.491-494
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    • 2006
  • The output performance characteristics for surveyed sites were analyzed, using developed model. It consists of two main parts, the deciding flow duration characteristic of river and performance prediction model to estimate the output characteristics of small hydropower plants. As a result, it was found that the flowrate concerning with 25% of time ratio on flow duration curve can be selected to design flowrate of small hydropower plants, and the output characteristics of small hydropower plants having overflow dam are different from large scale hydropower plants.

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Prediction System on Chance of Rain by Fuzzy Relational Model

  • Sano, Manabu;Tanaka, Kazuo;Yoshioka, Keisuke
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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    • pp.1222-1225
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    • 1993
  • The purpose of this paper is to construct a prediction system on the chance of rain in a local region using a fuzzy relational model. The prediction system consists of two parts. One is a prediction part on the chance of rain. The compositional law of fuzzy inference, proposed by Zadeh, is applied to predict the chance of rain. The other is a learning part of a fuzzy relational model using input-output data. A simple and fast learning algorithm is used in this part. Simulations are carried out by the actual weather data in our city and their results show the validity of prediction by the fuzzy relational approach.

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데이터간 의미 분석을 위한 R기반의 데이터 가중치 및 신경망기반의 데이터 예측 모형에 관한 연구 (A Novel Data Prediction Model using Data Weights and Neural Network based on R for Meaning Analysis between Data)

  • 정세훈;김종찬;심춘보
    • 한국멀티미디어학회논문지
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    • 제18권4호
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    • pp.524-532
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    • 2015
  • All data created in BigData times is included potentially meaning and correlation in data. A variety of data during a day in all society sectors has become created and stored. Research areas in analysis and grasp meaning between data is proceeding briskly. Especially, accuracy of meaning prediction and data imbalance problem between data for analysis is part in course of something important in data analysis field. In this paper, we proposed data prediction model based on data weights and neural network using R for meaning analysis between data. Proposed data prediction model is composed of classification model and analysis model. Classification model is working as weights application of normal distribution and optimum independent variable selection of multiple regression analysis. Analysis model role is increased prediction accuracy of output variable through neural network. Performance evaluation result, we were confirmed superiority of prediction model so that performance of result prediction through primitive data was measured 87.475% by proposed data prediction model.

신.재생에너지 인력수요전망 방법론 및 사례 연구 (Methods to Predict Demand for Workforce in New & Renewable Energy Industry)

  • 이유아;허은녕
    • 신재생에너지
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    • 제7권3호
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    • pp.36-45
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    • 2011
  • Prediction of demand for workforce in new and renewable energy is precondition for sustainable growth of an industry. The purpose of this research is to review prediction methods and case studies of workforce in new and renewable energy industry. This research compares the three methods in the focused on possibility of applying in renewable energy industry; survey, input-output and labor function estimation methods. Also, three cases are reviewed in the focused on applied method; Korea, America and Australia. As a result, the survey method was wildly used in the new and renewable industry. Also the improvement rates of work force are difference depending on the methodology. This result can be applied to set up the policy of human resource development of renewable energy.

Does Specialization Matter for Trade Imbalance at Industry Level?

  • Song, E. Young;Zhao, Chen
    • East Asian Economic Review
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    • 제16권3호
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    • pp.227-247
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    • 2012
  • This paper investigates the source of bilateral trade imbalance at industry level. We build a simple model based on gravity theory and derive the prediction that the bilateral trade balance in an industry is increasing in the difference between trading partners in the output share of the industry. We test this prediction and find that the difference in industry share is highly significant in predicting both the sign and the magnitude of trade balance at industry level. We also find that FTAs tend to enlarge trade imbalance at industry level. However, the overall predictive power of the model is rather limited, suggesting that factors other than production specialization are important in determining trade balance at industry level. Another finding of the paper is that the influence of the difference in industry share on trade balance increases as we move to industries that produce more homogeneous products. This finding calls into question monopolistic competition as the main driver of gravity in international trade.

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A Novel Predictive Digital Controlled Sensorless PFC Converter under the Boundary Conduction Mode

  • Wang, Jizhe;Maruta, Hidenori;Matsunaga, Motoshi;Kurokawa, Fujio
    • Journal of Power Electronics
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    • 제17권1호
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    • pp.1-10
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    • 2017
  • This paper presents a novel predictive digital control method for boundary conduction mode PFC converters without the need for detecting the inductor current. In the proposed method, the inductor current is predicted by analytical equations instead of being detected by a sensing-resistor. The predicted zero-crossing point of the inductor current is determined by the values of the input voltage, output voltage and predicted inductor current. Importantly, the prediction of zero-crossing point is achieved in just a single switching cycle. Therefore, the errors in predictive calculation caused by parameter variations can be compensated. The prediction of the zero-crossing point with the proposed method has been shown to have good accuracy. The proposed method also shows high stability towards variations in both the inductance and output power. Experimental results demonstrate the effectiveness of the proposed predictive digital control method for PFC converters.

9 kW 출력용 태양열 스털링엔진 발전시스템의 설계와 성능예측 (Design and Performance Prediction of Power System in a Solar Stirling Engine for 9 kW Output)

  • 배명환;강상율
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2003년도 춘계학술대회
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    • pp.2198-2204
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    • 2003
  • In order to make a match of the insufficient direct solar radiation, in this study, the target output is lowered to 9 kW smaller than 25 kW in former studies. It is also necessary to match the collector/receiver with engine/generator systems to accomplish the power level of a system. The simulation analyses of a dish solar power system with stirling engine are totally carried out to predict the system performance with the designed values. In addition, an influence of direct solar radiation on system performance and operation control is discussed in simulation. It is found that the diameter of concentrator could be made small to 8 m regardless of slope errors with 2.5 and 5.0 mrad radiation, and the operation range of mean pressure control. is wide even if the direct solar radiation is a quit low.

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GOV구조를 이용한 MPEG-4 비트율 제어기법 (MPEG-4 Rate Control Using GOV Structure)

  • 박지호;김종호;정제창
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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    • pp.2056-2059
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    • 2003
  • The rate control is very important to solve the difficulties arising from bit-rate on transmission through channel and to improve video quality. It is very important to point out that the amount of output bit obtained the encoding process using rate controller brings many problems on the transmission of channels and furthermore output bitstream decoded affects directly on the visual quality of displayed subject. In this paper, the effective rate control algorithm by rate-distortion modeling using MPEG-4 encoder is proposed. The proposed rate control has applied different weighting by VOP prediction type and even in the same VOP prediction type, the predicted reference allocates more bit. Through these bit allocation the minimization of distortion can be achieved preventing propagation of quantization error The amount of saved bitstream obtained by the proposed algorithm in this thesis is allocated to I-VOP using region of interest(ROI) selective enhancement on the next GOV encoding process and this process brought the improvement of visual quality.

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Lifetime prediction of optocouplers in digital input and output modules based on bayesian tracking approaches

  • Shin, Insun;Kwon, Daeil
    • Smart Structures and Systems
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    • 제22권2호
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    • pp.167-174
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    • 2018
  • Digital input and output modules are widely used to connect digital sensors and actuators to automation systems. Digital I/O modules provide flexible connectivity extension to numerous sensors and actuators and protect systems from high voltages and currents by isolation. Components in digital I/O modules are inevitably affected by operating and environmental conditions, such as high voltage, high current, high temperature, and temperature cycling. Because digital I/O modules transfer signals or isolate the systems from unexpected voltage and current transients, their failures may result in signal transmission failures and damages to sensitive circuitry leading to system malfunction and system shutdown. In this study, the lifetime of optocouplers, one of the critical components in digital I/O modules, was predicted using Bayesian tracking approaches. Accelerated degradation tests were conducted for collecting the critical performance parameter of optocouplers, current transfer ratio (CTR), during their lifetime. Bayesian tracking approaches, including extended Kalman filter and particle filter, were applied to predict the failure. The performance of each prognostic algorithm was then compared using accuracy and robustness-based performance metrics.