• Atmosphere
• /
• v.27 no.1
• /
• pp.17-28
• /
• 2017

The sensitivity of the typhoon track and intensity simulation to physics schemes of the global model are examined for the typhoon Bolaven and Tembin cases by using the Global/Regional Integrated Model System-Global Model Program (GRIMs-GMP) with the physics package version 2.0 of the Korea Institute of Atmospheric Prediction Systems. Microphysics, Cloudiness, and Planetary boundary Layer (PBL) parameterizations are changed and the impact of each scheme change to typhoon simulation is compared with the control simulation and observation. It is found that change of microphysics scheme from WRF Single-Moment 5-class (WSM5) to 1-class (WSM1) affects to the typhoon simulation significantly, showing the intensified typhoon activity and increased precipitation amount, while the effect of the prognostic cloudiness and PBL enhanced mixing scheme is not noticeable. It appears that WSM1 simulates relatively unstable and drier atmospheric structure than WSM5, which is induced by the latent heat change and the associated radiative effect due to not considering ice cloud. And WSM1 results the enhanced typhoon intensity and heavy rainfall simulation. It suggests that the microphysics is important to improve the capability for typhoon simulation of a global model and to increase the predictability of medium range forecast.

• Atmosphere
• /
• v.32 no.3
• /
• pp.191-206
• /
• 2022

Assimilation trials were performed using the Korea Institute of Atmospheric Prediction Systems (KIAPS) Korea Integrated Model (KIM) semi-operational forecast system to assess the impact of ground-based Global Navigation Satellite System (GNSS) Zenith Total Delay (ZTD) on forecast. To use the optimal observation in data assimilation of KIM forecast system, in this study, the ZTD observation were pre-processed. It involves the bias correction using long term background of KIM, the quality control based on background and the thinning of ZTD data. Also, to give the effect of observation directly to data assimilation, the observation operator which include non-linear model, tangent linear model, adjoint model, and jacobian code was developed and verified. As a result, impact of ZTD observation in both analysis and forecast was neutral or slightly positive on most meteorological variables, but positive on geopotential height. In addition, ZTD observations contributed to the improvement on precipitation of KIM forecast, specially over 5 mm/day precipitation intensity.

• KIEAE Journal
• /
• v.17 no.4
• /
• pp.83-88
• /
• 2017

Purpose: The objective of this study is to develop a predictive model for calculating the amount of cooling load for the different setback temperatures during the setback period. An artificial neural network (ANN) is applied as a predictive model. The predictive model is designed to be employed in the control algorithm, in which the amount of cooling load for the different setback temperature is compared and works as a determinant for finding the most energy-efficient optimal setback temperature. Method: Three major steps were conducted for proposing the ANN-based predictive model - i) initial model development, ii) model optimization, and iii) performance evaluation. Result:The proposed model proved its prediction accuracy with the lower coefficient of variation of the root mean square errors (CVRMSEs) of the simulated results (Mi) and the predicted results (Si) under generally accepted levels. In conclusion, the ANN model presented its applicability to the thermal control algorithm for setting up the most energy-efficient setback temperature.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.723-727
• /
• 2003

In this paper, two methods are discussed for good rolling force prediction in a plate mill. One is about the development of a long and a short learning scheme using a Neural Network for normal rolling and the other is about a mathematical model improvement by considering microstructural changes for controlled rolling. The research results are implemented in a on-line system of Pohang Works in POSCO and the field tests have showed that the prediction accuracies of rolling force are highly improved.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.4
• /
• pp.315-319
• /
• 2007

A technique to model plasma processes was presented. This was accomplished by combining the backpropagation neural network (BPNN) and genetic algorithm (GA). Particularly, the GA was used to optimize five training factor effects by balancing the training and test errors. The technique was evaluated with the plasma etch data, characterized by a face-centered Box Wilson experiment. The etch outputs modeled include Al etch rate, AI selectivity, DC bias, and silica profile angle. Scanning electron microscope was used to quantify the etch outputs. For comparison, the etch outputs were modeled in a conventional fashion. GABPNN models demonstrated a considerable improvement of more than 25% for all etch outputs only but he DC bias. About 40% improvements were even achieved for the profile angle and AI etch rate. The improvements demonstrate that the presented technique is effective to improving BPNN prediction performance.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.359-362
• /
• 1996

The guidance system which uses the line-of-sight(LOS) rate to guide the missile towards its target has been used to the conventional differential game, such as the pursuer-evader game. Proportional navigation guidance and its derivatives have been shown to be an effective LOS rate guidance system. In this paper, we have used the genetic algorithm to construct the guidance system for the pursuer-evader type differential game. Also we have proposed the prediction model to obtain the informations about the intention of future actions of the pursuer and the evader.

• Journal of Power Electronics
• /
• v.16 no.1
• /
• pp.319-328
• /
• 2016

In this study, we first briefly introduce the effect of circulating current control on the modulation signal of a modular multilevel converter (MMC). The maximum modulation index is also theoretically derived. According to the optimal modulation index analysis and the model in the continuous domain, different DC-side output impedance equivalent models of MMC with/without compensating component are derived. The DC-side impedance of MMC inverter station can be regarded as a series xR + yL + zC branch in both cases. The compensating component of the maximum modulation index is also related to the DC equivalent impedance with circulating current control. The frequency characteristic of impedance for MMC, which is observed from its DC side, is analyzed. Finally, this study investigates the prediction of the DC voltage ripple transfer between two-terminal MMC high-voltage direct current systems under unbalanced conditions. The rationality and accuracy of the impedance model are verified through MATLAB/Simulink simulations and experimental results.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10b
• /
• pp.440-445
• /
• 1992

The major purpose here is to estimate the drying time required in the fish-drying process employed. The basic element of the prediction of the drying time is the model or the equation, which governs the change in weight. By an intuitive consideration on the mechanism of dehydration, a mathematical model of the fish-drying process is built, which is described by a system of linear differential equations. Further, a modified system of linear differential equations for a model of drying is also proposed for more accurate estimation. The parameter estimation of this system of equations provides the prediction of necessary drying time.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.6
• /
• pp.1562-1582
• /
• 2024

The prediction of pedestrian trajectory is conducive to reducing traffic accidents and protecting pedestrian safety, which is crucial to the task of intelligent driving. The existing methods mainly use the past pedestrian trajectory to predict the future deterministic pedestrian trajectory, ignoring pedestrian intention and trajectory diversity. This paper proposes a multi-modal trajectory prediction model that introduces pedestrian intention. Unlike previous work, our model makes multi-modal goal-conditioned trajectory pedestrian prediction based on the past pedestrian trajectory and pedestrian intention. At the same time, we propose a novel Gate Recurrent Unit (GRU) to process intention information dynamically. Compared with traditional GRU, our GRU adds an intention unit and an intention gate, in which the intention unit is used to dynamically process pedestrian intention, and the intention gate is used to control the intensity of intention information. The experimental results on two first-person traffic datasets (JAAD and PIE) show that our model is superior to the most advanced methods (Improved by 30.4% on MSE_0.5s and 9.8% on MSE_1.5s for the PIE dataset; Improved by 15.8% on MSE_0.5s and 13.5% on MSE_1.5s for the JAAD dataset). Our multi-modal trajectory prediction model combines pedestrian intention that varies at each prediction time step and can more comprehensively consider the diversity of pedestrian trajectories. Our method, validated through experiments, proves to be highly effective in pedestrian trajectory prediction tasks, contributing to improving traffic safety and the reliability of intelligent driving systems.

• Journal of the Korea Institute of Building Construction
• /
• v.16 no.4
• /
• pp.297-303
• /
• 2016

Shrinkage Reducing Agent(SRA) was developed in order to control drying shrinkage cracks in concrete, and the use of SRA is increasing since it can control drying shrinkage cracks and improve the quality of concrete structures. Although there are many types of prediction equations of drying shrinkage strain, there is no prediction method which can consider the effect of SRA up to the present. Therefore, it is impossible to predict the tensile stress generated by drying shrinkage of SRA concrete, and to investigate the quantitative serviceability limit state of SRA concrete. In this study, the drying shrinkage of SRA concrete was investigated by experiment and analysis in order to suggest the predictability of drying shrinkage of SRA concrete. As a result, AIJ model, ACI model, GL2000 model showed there was a correlation between the predicted values and the experimental values within the error range of ${\pm}10%$. However, CEB-FIP model and B3 model underestimated the experimental values.