• International Journal of Automotive Technology
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• v.7 no.7
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• pp.813-819
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• 2006

As the vehicle becomes bigger and faster, the importance of vehicle stability in an extreme driving condition caused by sudden steering, road condition or unexpected case has been emphasized. The ESP system is being utilized to improve the handling performance and the vehicle stability. In this study, we implemented various tests and proposed estimation methods for ESP characteristics in extreme driving situations. The estimation methods for ESP proposed in this paper are expected to facilitate developing the control logic and improving the performance of the ESP system.

• Journal of Korea Water Resources Association
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• v.51 no.6
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• pp.523-533
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• 2018

The objective of this study is to analyze uncertainties of ensemble-based streamflow prediction method for model parameters and input data. ESP (Ensemble Streamflow Prediction) and BAYES-ESP (Bayesian-ESP) based on ABCD rainfall-runoff model were selected as streamflow prediction method. GLUE (Generalized Likelihood Uncertainty Estimation) was applied for the analysis of parameter uncertainty. The analysis of input uncertainty was performed according to the duration of meteorological scenarios for ESP. The result showed that parameter uncertainty was much more significant than input uncertainty for the ensemble-based streamflow prediction. It also indicated that the duration of observed meteorological data was appropriate to using more than 20 years. And the BAYES-ESP was effective to reduce uncertainty of ESP method. It is concluded that this analysis is meaningful for elaborating characteristics of ESP method and error factors of ensemble-based streamflow prediction method.

• Magazine of the Korean Society of Agricultural Engineers
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• v.31 no.1
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• pp.96-105
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• 1989

This laboratory study was performed to produce basic data for the estimation of water requirements for desalinization, through analyzing changes of the electrical conductivity and the exchangeable sodium percentage during the desalinization of reclaimed tidelands. Desalinization experiments were carried out by two water management practices, namely, the leaching method by subsurface drainage and the rinsing method by surface drainage, using samples of silt loam soil and silty clay loam soil collected in reclaimed tidelands. The results obtained from this study were summarized as follows : 1. The sample soils used in this study were saline-sodic soils with the high electrical conductivity and the high exchangeable sodium percentage. 2. Changes of the electrical conductivity and the exchangeable sodium percentage with water requirements for desalinization showed a similar tendency in the desalinization experiment by the same water management practice. 3. The regression equation between the relative electrical conductivity(EC/EC) and water requirements for desalinization(Dw/Ds) could be described by Dw/Ds=O. 29x(EC/EC.) -0.982 (Leaching method), Dw/Ds=3. 678X0. 030(EC/EC ) (Rinsing method). 4. The regression equation between the relative exchangeable sodium percentage (ESP/ESP ) and water requirements for desalinization (Dw/Ds) could be expressed in Dw/Ds = 0.039 x (ESP/ESP. ) - 1. 134 (Leaching method), Dw/Ds=7. 197X0. 024(ESP/ESP ) (Rinsing method). 5. It was estimated that water requirements for the adequate desalinization would be Dw/Ds=0.3 (Leaching method) and Dw/Ds=3.0 (Rinsing method)

• Journal of Korean Society on Water Environment
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• v.27 no.3
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• pp.264-272
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• 2011

The objective of this study was to develop a model for predicting long-term runoff in a basin using the ensemble streamflow prediction (ESP) technique and review its reliability. To achieve the objective, this study improved not only the ESP technique based on the ensemble scenario analysis of historical rainfall data but also conventional ESP techniques used in conjunction with qualitative climate forecasting information, and analyzed and assessed their improvement effects. The model was applied to the Geum River basin. To undertake runoff forecasting, this study tried three cases (case 1: Climate Outlook + ESP, case 2: ESP probability through monthly measured discharge, case 3: Season ESP probability of case 2) according to techniques used to calculate ESP probabilities. As a result, the mean absolute error of runoff forecasts for case 1 proposed by this study was calculated as 295.8 MCM. This suggests that case 1 showed higher reliability in runoff forecasting than case 2 (324 MCM) and case 3 (473.1 MCM). In a discrepancy-ratio accuracy analysis, the Climate Outlook + ESP technique displayed 50.0%. This suggests that runoff forecasting using the Climate Outlook +ESP technique with the lowest absolute error was more reliable than other two cases.

• Journal of Drive and Control
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• v.16 no.4
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• pp.48-55
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• 2019

The Electronic Stability Program (ESP), a system that improves vehicle safety, also known as YMC (Yaw Motion Controller) or VDC (Vehicle Dynamics Control), is a system that operates in unstable or sudden driving and braking situations. Developing conditions such as unstable or sudden driving and braking situations in a vehicle are very dangerous unless you are an experienced professional driver. Additionally, many repetitive tests are required to collect reliable data, and there are many variables to consider such as changes in the weather, road surface, and tire condition. To overcome this problem, in this paper, hardware and control software such as the ESP controller, vehicle engine, ABS, and TCS module, composed of three control zones, are modeled using MATLAB/SIMULINK, and the vehicle, climate, and road surface. Various environmental variables such as the driving course were modeled and studied for the real-time ESP real-time simulator that can be repeatedly tested under the same conditions.

• Journal of Korea Water Resources Association
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• v.44 no.12
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• pp.967-974
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• 2011

Based on daily time series from RDAPS numerical weather forecast, Streamflow prediction was simulated and the result of ESP analysis was implemented considering quantitative mid- and long-term forecast to compare the results and review applicability. The result of ESP, ESP considering quantitative weather forecast, and flow forecast from RDAPS numerical weather forecast were compared and analyzed with average observed streamflow in Guem River Basin. Through this process, the improvement effect per method was estimated. The result of ESP considering weather information was satisfactory relatively based on long-term flow forecast simulation result. Discrepancy ratio analysis for estimating accuracy of probability forecast had similar result. It is expected to simulate more accurate flow forecast for RDAPS numerical weather forecast with improved daily scenario including time resolution, which is able to accumulate 3 hours rainfall or continuous simulation estimation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1B
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• pp.21-27
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• 2011

When execute runoff forecasting, can not remove perfectly uncertainty of forecasting results. But, reduce uncertainty by various techniques analysis. This study applied various forecasting techniques for runoff prediction's accuracy elevation in Gongju basin. statics techniques is ESP, Period Average & Moving average, Exponential Smoothing, Winters, Auto regressive moving average process. Authoritativeness estimation with results of runoff forecasting by each techniques used MAE (Mean Absolute Error), RMSE (Root Mean Squared Error), RRMSE (Relative Root Mean Squared Error), Mean Absolute Percentage Error (MAPE), TIC (Theil Inequality Coefficient). Result that use MAE, RMSE, RRMSE, MAPE, TIC and confirm improvement effect of runoff forecasting, ESP techniques than the others displayed the best result.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.60 no.4
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• pp.236-240
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• 2011

Currently one of the most importance issues in industrial sector is energy cost and energy efficiency. The manufacturing plants especially have made many efforts to reduce energy cost by implementing maintenances. But in many cases, they are not aware that how much energy could be saved more. If we know the best energy consumption, which signifies energy baseline, we can control the intensity of maintenances. One way to obtain the baseline is using proper statistics from a specific plant, a sector of industry. Energy bandwidth signifies the gap between actual Specific Energy Consumption(SEC) of a certain plant and minimum SEC of the best plant, and estimate energy saving potential(ESP) is a result of bandwidth analysis. We chose a model plant and implemented some maintenance for a year, and then we obtained ESP. Additionally we could determine the decreased amount of carbon emissions from the plant using Carbon Emissions Factor(CEF) by Intergovernmental Panel on Climate Change(IPCC).

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1765-1770
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• 2005

Recently, particle filters have attracted attentions for nonlinear state estimation. In this approaches, a posterior probability distribution of the state variable is evaluated based on observations in simulation using so-called importance sampling. We proposed a new filter, Evolution Strategies based particle (ESP) filter to circumvent degeneracy phenomena in the importance weights, which deteriorates the filter performance, and apply it to simultaneous state and parameter estimation of nonlinear state space models. Results of numerical simulation studies illustrate the applicability of this approach.

• Journal of Soil and Groundwater Environment
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• v.17 no.6
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• pp.69-81
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• 2012

Diverse geostatistical tools such as kriging have been used to estimate the volume and spatial coverage of contaminated soil needed for remediation. However, many approaches frequently yield estimation errors, due to inherent geostatistical uncertainties. Such errors may yield over- or under-estimation of the amounts of polluted soils, which cause an over-estimation of remediation cost as well as an incomplete clean-up of a contaminated land. Therefore, it is very important to use a better estimation tool considering uncertainties arising from incomplete field investigation (i.e., contamination survey) and mathematical spatial estimation. In the current work, as better estimation tools we propose stochastic simulation approaches which allow the remediation volume to be assessed more accurately along with uncertainty estimation. To test the efficiency of proposed methods, heavy metals (esp., Pb) contaminated soil of a shooting range area was selected. In addition, we suggest a quantitative method to delineate the confident interval of estimated volume (and spatial extent) of polluted soil based on the spatial aspect of uncertainty. The methods proposed in this work can improve a better decision making on soil remediation.