• Journal of Navigation and Port Research
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• v.29 no.4
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• pp.299-304
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• 2005

A simulation system is needed to train students and mariners in order that they can take suitable actions to evade typhoon's strike promptly and sufficiently. In order to make such kind of system, three kinds of models about the typhoon are necessary, typhoon prediction model to generate typhoon's track, wind & wave-field model to make sea conditions around the typhoon and evaluation model of trainee's action whether their actions were suitable or not during simulation. We have developed the prediction and wind & wave-field models of typhoon, but the evaluation model has not been developed yet. In this paper, after making a method for evaluating trainee's actions by seakeeping performance, we propose an typhoon avoidance simulation system for training mariners so that they can promote their abilities to evade the typhoons at sea.

• Journal of Korea Spatial Information System Society
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• v.8 no.1 s.16
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• pp.17-25
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• 2006

TPR*-tree is the most widely-used index structure for effectively predicting the future positions of moving objects. The TPR*-tree, however, has the problem that both of the dead space in a bounding region and the overlap among hounding legions become larger as the prediction time in the future gets farther. This makes more nodes within the TPR*-tree accessed in query processing time, which incurs the performance degradation. In this paper, we examine the performance problem quantitatively with a series of experiments. First, we show how the performance deteriorates as a prediction time gets farther, and also show how the updates of positions of moving objects alleviates this problem. Our contribution would help provide Important clues to devise strategies improving the performance of TPR*-trees further.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1041-1044
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• 1999

In This paper, we investigated the single step prediction for output responses of chaotic system with multi Input multi output using chaotic neural networks. Since the systems with chaotic characteristics are coupled between internal parameters, the chaotic neural networks is very suitable for output response prediction of chaotic system. To evaluate the performance of the proposed neural network predictor, we adopt for Lorenz attractor with chaotic responses and compare the results with recurrent neural networks. The results demonstrated superior performance on convergence and computation time than the predictor using recurrent neural networks. And we could also see good predictive capability of chaotic neural network predictor.

• Atmosphere
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• v.28 no.3
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• pp.263-272
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• 2018

The high-resolution ocean surface wind vector produced by scatterometer was assimilated within the Local Ensemble Transform Kalman Filter (LETKF) in Korea Institute of Atmospheric Prediction Systems (KIAPS). The Advanced Scatterometer (ASCAT) on Metop-A/B wind data was processed in the KIAPS Package for Observation Processing (KPOP), and a module capable of processing surface wind observation was implemented in the LETKF system. The LETKF data assimilation cycle for evaluating the performance improvement due to ASCAT observation was carried out for approximately 20 days from June through July 2017 when Typhoon Nepartak was present. As a result, we have found that the performance of ASCAT wind vector has a clear and beneficial effect on the data assimilation cycle. It has reduced analysis errors of wind, temperature, and humidity, as well as analysis errors of lower troposphere wind. Furthermore, by the assimilation of the ASCAT wind observation, the initial condition of the model described the typhoon structure more accurately and improved the typhoon track prediction skill. Therefore, we can expect the analysis field of LETKF will be improved if the Scatterometer wind observation is added.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1047-1056
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• 2022

Sea ice, frozen sea water, in the Artic is a primary indicator of global warming. Due to its importance to the climate system, shipping-route navigation, and fisheries, Arctic sea ice prediction has gained increased attention in various disciplines. Recent advances in artificial intelligence (AI), motivated by a desire to develop more autonomous and efficient future predictions, have led to the development of new sea ice prediction models as alternatives to conventional numerical and statistical prediction models. This study aims to evaluate the performance of the two-stream convolutional long-and short-term memory (TS-ConvLSTM) AI model, which is designed for learning both global and local characteristics of the Arctic sea ice changes, for the minimum September Arctic sea ice from 2001 to 2021, and to show the possibility for an operational prediction system. Although the TS-ConvLSTM model generally increased the prediction performance as training data increased, predictability for the marginal ice zone, 5-50% concentration, showed a negative trend due to increasing first-year sea ice and warming. Additionally, a comparison of sea ice extent predicted by the TS-ConvLSTM with the median Sea Ice Outlooks (SIOs) submitted to the Sea Ice Prediction Network has been carried out. Unlike the TS-ConvLSTM, the median SIOs did not show notable improvements as time passed (i.e., the amount of training data increased). Although the TS-ConvLSTM model has shown the potential for the operational sea ice prediction system, learning more spatio-temporal patterns in the difficult-to-predict natural environment for the robust prediction system should be considered in future work.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.3 no.4
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• pp.231-240
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• 1991

A design method has been developed for a Stirling engine with a tubular heater and cooler and a screen type regenerator. This paper provides a design procedure to determine the thermodynamic states and the geometric configurations of the Stirling engine for residential heat pumps. The major design is concerned with the working spaces, i.e. compression and expansion spaces and the heat exchangers such as the heater, the cooler and the regenerator. The Schmidt analysis has been employed to obtain the mass flow rates and heat transfer requirements of the system. The performance analysis of a model Stirling engine was performed by Martini-Weiss program to prove the validity of this design method. The results obtained indicate that this design method is valid for the Stirling engine conceptual design and performance analysis.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.647-652
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• 2000

This paper proposes a collision warning/avoidance algorithm using a trajectory prediction method. This algorithm is based on 2-dimensional kinematics and the Kalman filter has been used to obtain the information of the object vehicle. This algorithm has been investigated via computer simulation and showed a good trajectory prediction performance. The proposed collision warning/avoidance algorithm would enhanced driver acceptance for a collision warning/avoidance system.

• Industrial Engineering and Management Systems
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• v.14 no.3
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• pp.312-317
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• 2015

The dynamic system approach in time series has been used in many real problems. Based on Taken's embedding theorem, we can build the predictive function where input is the time delay coordinates vector which consists of the lagged values of the observed series and output is the future values of the observed series. Although the time delay coordinates vector from multivariate time series brings more information than the one from univariate time series, it can exhibit statistical redundancy which disturbs the performance of the prediction function. We apply dimension reduction techniques to solve this problem and analyze the effect of this approach for prediction. Our experiment uses delayed Lorenz series; least squares support vector regression approximates the predictive function. The result shows that linearly preserving projection improves the prediction performance.

• Proceedings of the SAREK Conference
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• 2005.11a
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• pp.294-299
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• 2005

In order to control indoor air quality and save energy. it is needed to install a suitable ventilation system equipped with heat exchanger for heat recovery. Paper heat exchanger can recover $50{\sim}70$ of the enthalpy difference between supply and exhaust air. The purpose of this research is to obtain the experimental correlations for the friction factor, heat transfer coefficient, mass transfer coefficient and permeance of paper heat exchanger, which can be used for the performance prediction of the paper heat exchanger. Pressure drop at various velocities and heat transfer rate at various dry-bulb temperatures, relative humidities, and specific humidities are measured to make experimental correlations. The results of prediction using correlations show fairly good agreement with experimental data.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.31 no.3
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• pp.59-70
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• 2023

In order to predict low-level wind shear at Incheon International Airport (RKSI), a Low-Level Wind Shear prediction system (KMAP-LLWS) along the runway take-off and landing route at RKSI was established using Korea Meteorological Administration Post-Processing (KMAP). For the performance evaluation, the case of low-level wind shear cases calculated from Aircraft Meteorological Data Relay (AMDAR) from July 2021 to June 2022 was used. As a result of verification using the performance evaluation index, POD, FAR, CSI, and TSS were 0.5, 0.85, 0.13, and 0.34, respectively, and the prediction performance was improved by POD, CSI, and TSS compared to the Low-Level Wind Shear prediction system (LDPS-LLWS) calculated using the Korea Meteorological Administration's Local Data Assimilation and Prediction System (LDAPS). This means that the use of high-resolution numerical models improves the predictability of wind changes. In addition, to improve the high FAR of KMAP-LLWS, the threshold for low-level wind shear strength was adjusted. As a result, the most effective low-level wind shear threshold at 8.5 knot/100 ft was derived. This study suggests that it is possible to predict and respond to low-level wind shear at RKSI. In addition, it will be possible to predict low-level wind shear at other airports without wind shear observation equipment by applying the KMAP-LLWS.