• Title/Summary/Keyword: Demand estimation

Search Result 833, Processing Time 0.021 seconds

Prediction of Volumes and Estimation of Real-time Origin-Destination Parameters on Urban Freeways via The Kalman Filtering Approach (칼만필터를 이용한 도시고속도로 교통량예측 및 실시간O-D 추정)

  • 강정규
    • Journal of Korean Society of Transportation
    • /
    • v.14 no.3
    • /
    • pp.7-26
    • /
    • 1996
  • The estimation of real-time Origin-Destination(O-D) parameters, which gives travel demand between combinations of origin and destination points on a urban freeway network, from on-line surveillance traffic data is essential in developing an efficient ATMS strategy. On this need a real-time O-D parameter estimation model is formulated as a parameter adaptive filtering model based on the extended Kalman Filter. A Monte Carlo test have shown that the estimation of time-varying O-D parameter is possible using only traffic counts. Tests with field data produced the interesting finding that off-ramp volume predictions generated using a constant freeway O-D matrix was replaced by real-time estimates generated using the parameter adaptive filter.

  • PDF

A Study on the Parameter Estimation of Solar Cell Module (태양전지 모듈의 파라미터 추정에 관한 연구)

  • Kim, Tae-Yeop;Lee, Yun-Gyu;An, Ho-Gyun
    • The Transactions of the Korean Institute of Electrical Engineers B
    • /
    • v.51 no.2
    • /
    • pp.92-98
    • /
    • 2002
  • It is necessary to measure the solar cell parameter fur understanding characteristic of solar cell and applying to many other fields. Since photovoltaic system consists of solar cell module, which are connected each other in series and parallel, it is not proper to apply a solar cell parameter to photovoltaic system. Therefore, to estimate the solar tell module and to solve the problem of the established algorithm is on demand. In this paper the authors have improved the accuracy of solar cell module Parameter estimation by compensating series and Parallel resistance, and developed a new parameter estimation algorithm, which can be applied to photovoltaic system without high cost measuring equipment. And the validity of proposed algorithm is verified by the simulation and experimentation.

An Empirical Study on Determining Factors of estimation cost: Focused on Defense Goods (예정가격 결정요인에 관한 연구: 방산물자를 중심으로)

  • Song, Young-Il;Kim, Dong-Uk;Shim, Suk-Hwa
    • Journal of the military operations research society of Korea
    • /
    • v.37 no.1
    • /
    • pp.99-118
    • /
    • 2011
  • According to the National Contract Law, when determining Estimation cost Contract officers should consider contract quantity, contract period, supply and demand condition, difficulty of contract enforcement, terms and condition, and other various conditions based market price, costing based pricing, and appraisal. And they should not overestimate or underestimate the estimation cost. But the estimation cost system is used as preparedness for audit against the contract law. In this study, we identified the factors affecting estimation cost and analyzed their influence on estimation cost.

Real-Time Haptic Rendering for Multi-contact Interaction with Virtual Environment (가상현실을 위한 다중 접촉 실시간 햅틱 랜더링)

  • Lee, Kyung-No;Lee, Doo-Yong
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.14 no.7
    • /
    • pp.663-671
    • /
    • 2008
  • This paper presents a real-time haptic rendering method for multi-contact interaction with virtual environments. Haptic systems often employ physics-based deformation models such as finite-element models and mass-spring models which demand heavy computational overhead. The haptic system can be designed to have two sampling times, T and JT, for the haptic loop and the graphic loop, respectively. A multi-rate output-estimation with an exponential forgetting factor is proposed to implement real-time haptic rendering for the haptic systems with two sampling rates. The computational burden of the output-estimation increases rapidly as the number of contact points increases. To reduce the computation of the estimation, the multi-rate output-estimation with reduced parameters is developed in this paper. Performance of the new output-estimation with reduced parameters is compared with the original output-estimation with full parameters and an exponential forgetting factor. Estimated outputs are computed from the estimated input-output model at a high rate, and trace the analytical outputs computed from the deformation model. The performance is demonstrated by simulation with a linear tensor-mass model.

Development of Optimal Number of Bus-stops Estimation Model Based on On-Off Patterns of Passengers (버스승객의 승하차 패턴을 고려한 최적 정류장 수 산정 모형 개발)

  • Gang, Ju-Ran;Go, Seung-Yeong
    • Journal of Korean Society of Transportation
    • /
    • v.24 no.1 s.87
    • /
    • pp.97-108
    • /
    • 2006
  • At present, Korean many cities depend on subjective judgements of experts to estimate the number of bus-stops and inter-stop space. To get reliable results by using more objective procedure, we search for old studies and models, but they don't concern alighting demands and a random demand distributions. Our study recognize and overcome these limitation. We devide the demand into boarding and alighting demands, and define the model that can estimate flexibly optimal number of bus-stop and inter-stop space on each segment by the demand distribution. Also we apply this new model to a simple example route having various demand distributions As a result, the number of bus-stop on each segment can be estimate flexibly in proportion to boarding or alighting demand by using this model.

Changes in Elasticities of Demand for Oil Products and Electricity in Korea (석유제품과 전력의 수요행태 변화에 대한 실증분석)

  • Kim, Youngduk;Park, Minsoo
    • Environmental and Resource Economics Review
    • /
    • v.22 no.2
    • /
    • pp.251-279
    • /
    • 2013
  • Prices of oil products such as gasoline and diesel are deregulated since 1997 while electricity price is still controlled by government. This difference may explain recent discrepancy in the patterns of demand for oil products and electricity - constant increase in electricity consumption and stagnant demand for oil. To verify it empirically, we estimate price and income (production) elasticity of demand across time by using a rolling regression with 10 year-window based on monthly data for 1981-2011. Estimation results show that the sensitivity to price in demand for gasoline and diesel has increased since mid-90s while the elasticity of demand for electricity has become smaller. Second, income (production) elasticities of demand have shown no significant changes for both oil products and electricity. Third, cross-price elasticity was found meaningful only for gasoline before mid 1990s and for diesel after then.

Estimation of Regional Future Agricultural Water Demand in Jeju Island Considering Land Use Change (토지이용 변화를 고려한 제주도 권역별 미래 농업용수 수요량 추정)

  • Song, Sung-Ho;Myoung, Woo-Ho;An, Jung-Gi;Jang, Jung-Seok;Baek, Jin-Hee;Jung, Cha-Youn
    • Journal of Soil and Groundwater Environment
    • /
    • v.23 no.1
    • /
    • pp.92-105
    • /
    • 2018
  • In this study, the projected land use area in 2030 for major crop production was estimated in Jeju Island using land cover map, and corresponding agricultural water demand for 40 sub-regions was quantitatively assessed using the future climate change scenario (RCP 4.5). Estimated basic unit of water demand in 2030 was the highest in the western region, and the lowest in the eastern region. Monthly maximum agricultural water demand analysis revealed that water demand in August of 2030 substantially increased, suggesting the climate of Jeju Island is changing to a subtropical climate in 2030. Agricultural water demand for sub-region in 2030 was calculated by multiplying the target area of the water supply excluding the area not in use in winter season by the basic unit of water demand, and the maximum and minimum values were estimated to be $306,626m^3/day$ at Seogwipo downtown region and $77,967m^3/day$ at Hallim region, respectively. Consequently, total agricultural water demand in Jeju Island in 2030 was estimated to be $1,848,010m^3/day$.

Social Cost Comparison of Air-Quality based on Various Traffic Assignment Frameworks (교통량 배정 방법에 따른 대기질의 사회적 비용 비교분석)

  • Lee, Kyu Jin;Choi, Keechoo
    • KSCE Journal of Civil and Environmental Engineering Research
    • /
    • v.33 no.3
    • /
    • pp.1087-1094
    • /
    • 2013
  • This study aims at enhancing the objective estimation of social cost of air quality due to mobile emission. More specifically, it examines the difference between the daily oriented and hourly oriented estimation results of social air quality cost and draws implications from the comparative analysis. The result indicates that the social cost of air quality differs up to approximately 24 times depending on the analysis time period. Moneywise, the difference between daily and hourly assignments amounts to the average of 653.5 billion won whereas only 1% of error occurred in the estimation result based on peak and nonpeak based hourly assignment. This study reaffirms the need for time-based travel demand management for emission reduction, and confirms the feasibility of emission estimation by travel demand forecasting method over the conventional method employed by the CAPSS.

Development and Evaluation of Regression Model for TOC Contentation Estimation in Gam Stream Watershed (감천 유역의 TOC 농도 추정을 위한 회귀 모형 개발 및 평가)

  • Jung, Kang-Young;Ahn, Jung-Min;Lee, Kyung-Lak;Kim, Shin;Yu, Jae-Jeong;Cheon, Se-Uk;Lee, In Jung
    • Journal of Environmental Science International
    • /
    • v.24 no.6
    • /
    • pp.743-753
    • /
    • 2015
  • In this study, it is an object to develop a regression model for the estimation of TOC (total organic carbon) concentration using investigated data for three years from 2010 to 2012 in the Gam Stream unit watershed, and applied in 2009 to verify the applicability of the regression model. TOC and $COD_{Mn}$ (chemical oxygen demand) were appeared to be derived the highest correlation. TOC was significantly correlated with 5 variables including BOD (biological oxygen demand), discharge, SS (suspended solids), Chl-a (chlorophyll a) and TP (total phosphorus) of p<0.01. As a result of PCA (principal component analysis) and FA (factor analysis), COD, TOC, SS, discharge, BOD and TP have been classified as a first factor. TOCe concentration was estimated using the model developed as an independent variable $BOD_5$ and $COD_{Mn}$. R squared value between TOC and measurement TOC is 0.745 and 0.822, respectively. The independent variable were added step by step while removing lower importance variable. Based on the developed optimal model, R squared value between measurement value and estimation value for TOC was 0.852. It was found that multiple independent variables might be a better the estimation of TOC concentration using the regression model equation(in a given sites).

Density map estimation based on deep-learning for pest control drone optimization (드론 방제의 최적화를 위한 딥러닝 기반의 밀도맵 추정)

  • Baek-gyeom Seong;Xiongzhe Han;Seung-hwa Yu;Chun-gu Lee;Yeongho Kang;Hyun Ho Woo;Hunsuk Lee;Dae-Hyun Lee
    • Journal of Drive and Control
    • /
    • v.21 no.2
    • /
    • pp.53-64
    • /
    • 2024
  • Global population growth has resulted in an increased demand for food production. Simultaneously, aging rural communities have led to a decrease in the workforce, thereby increasing the demand for automation in agriculture. Drones are particularly useful for unmanned pest control fields. However, the current method of uniform spraying leads to environmental damage due to overuse of pesticides and drift by wind. To address this issue, it is necessary to enhance spraying performance through precise performance evaluation. Therefore, as a foundational study aimed at optimizing drone-based pest control technologies, this research evaluated water-sensitive paper (WSP) via density map estimation using convolutional neural networks (CNN) with a encoder-decoder structure. To achieve more accurate estimation, this study implemented multi-task learning, incorporating an additional classifier for image segmentation alongside the density map estimation classifier. The proposed model in this study resulted in a R-squared (R2) of 0.976 for coverage area in the evaluation data set, demonstrating satisfactory performance in evaluating WSP at various density levels. Further research is needed to improve the accuracy of spray result estimations and develop a real-time assessment technology in the field.