• International Journal of Highway Engineering
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• v.20 no.2
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• pp.127-135
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• 2018

PURPOSES : This study develops various models that can estimate the pattern of road surface temperature changes using machine learning methods. METHODS : Both a thermal mapping system and weather forecast information were employed in order to collect data for developing the models. In previous studies, the authors defined road surface temperature data as a response, while vehicular ambient temperature, air temperature, and humidity were considered as predictors. In this research, two additional factors-road type and weather forecasts-were considered for the estimation of the road surface temperature change pattern. Finally, a total of six models for estimating the pattern of road surface temperature changes were developed using the MATLAB program, which provides the classification learner as a machine learning tool. RESULTS : Model 5 was considered the most superior owing to its high accuracy. It was seen that the accuracy of the model could increase when weather forecasts (e.g., Sky Status) were applied. A comparison between Models 4 and 5 showed that the influence of humidity on road surface temperature changes is negligible. CONCLUSIONS : Even though Models 4, 5, and 6 demonstrated the same performance in terms of average absolute error (AAE), Model 5 can be considered the optimal one from the point of view of accuracy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.5
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• pp.565-574
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• 2009

The water vapor weighted vertically mean temperature(Tm) models, which were developed by the consideration of seasonal characteristics over the Korea, was used in the retrieval of precipitable water vapor (PWV) from GPS data which were observed at four GPS permanent stations. Since the weighted mean temperature relates to the water vapor pressure and temperature profile at a site, the accuracy of water vapor information which were estimated from GPS tropospheric wet delay is proportional to the accuracy of the weighted mean temperature. The adaption of Korean seasonal weighted mean temperature model, as an alternative to other formulae which are suggested from other nation, provides an improvement in the accuracy of the GPS PWV estimation. Therefore, it can be concluded that the seasonally appropriate weighted mean temperature model, which is used to convert actual zenith wet delay (ZWD) to the PWV, can be more reduced the relative biases of PWV estimated from GPS signal delays in the troposphere than other annual model, so that it would be useful for GPS PWV estimation with high accuracy.

• Plant Journal
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• v.17 no.4
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• pp.41-52
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• 2021

In this study, the PV output and module temperature values were predicted using the Meteorological Agency data and compared with actual data, weather, solar radiation, ambient temperature, and wind speed. The forecast accuracy by weather was the lowest in the data on a clear day, which had the most data of the day when it was snowing or the sun was hit at dawn. The predicted accuracy of the module temperature and the amount of power generation according to the amount of insolation decreased as the amount of insolation increased, and the predicted accuracy according to the ambient temperature decreased as the module temperature increased as the ambient temperature increased and the amount of power generated lowered the ambient temperature. As for wind speed, the predicted accuracy decreased as the wind speed increased for both module temperature and power generation, but it was difficult to define the correlation because wind speed was insignificant than the influence of other weather conditions.

• Journal of the Korean Geographical Society
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• v.42 no.1 s.118
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• pp.1-14
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• 2007

This study aimed to evaluate weather forecast accuracies of minimum temperature, maximum temperature, precipitation and sky cover by the localized land forecast areas over South Korea Average forecast accuracy score of precipitation was the lowest while that of sky cover was the highest during the study period Overall forecast accuracy scores for Gangwon-do was the lowest while those for Gyeongsangnam-do and Gyeongsangbuk-do were higher than other areas. The frequencies of perfect forecast(eight points) by seasons, were the highest during winter and the lowest during summer. pressure pattern analyses for days when forecast accuracy scores were poor, showed that precipitation forecast accuracy scores were lower due to the movement of the stationary fronts during summers. When continental polar air masses expanded, forecast accuracy of temperature became greatly lower during autumns and winters As the migratory anticyclone pattern rapidly moved, forecast accuracy became lower during springs and autumns. Forecast accuracies were compared by wind directions at 850hPa for the Young-dong region where forecast accuracy was the lowest. Forecast accuracy scores on minimum and maximum temperatures were low when winds were westerlies and forecast accuracy scores of precipitation were low when winds were easterlies.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.4
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• pp.435-442
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• 2016

For inertial navigation systems, initial information such as position, velocity and attitude is required for navigation. Self-alignment is the process to determine initial attitude on stationary condition using inertial measurements such as accelerations and angular rates. The accuracy of self-alignment is determined by inertial sensor error. As soon as an inertial navigation system is powered on, the temperature of accelerometer rises rapidly until temperature stabilization. It causes acceleration error which is called temperature stabilizing error of accelerometer. Therefore, temperature stabilizing error degrades the alignment accuracy and also increases alignment time. This paper suggests a method to calculate azimuthal attitude using curve fitting of horizontal control angular rate in fixed-gain self-alignment. It is verified by simulation and experiment that the accuracy is improved and the alignment time is reduced using the proposed method under existence of the temperature stabilizing error.

• Magazine of the Korean Society of Agricultural Engineers
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• v.41 no.6
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• pp.25-32
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• 1999

The purpose of this study is to analyse the accuracy of weather forecasts of temperature, precipitation probability , and sky condition and to evaluate the applicability of weather forecasts for the estimation of potential evapotranspiration for irrigation scheduling. Five weather station s were selected to compare forecasted and measured climatcal data. The error between forecasted and measured temperature was calculated and discussed. The accuracy of temperature forecast using relative frequency of the error was calculated . The temperature forecasting showed considerably high accuracy. Average sunshine hours for forecasted sky conditions were calculated and showed reasonable quality. From the reliability graphs, the forecasting precipation probabililty was reliable. Potential evapotranspirations were calculated and compared using forecast and measured temperatures. The weather forecast is considered usable for irrigation scheculing.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.465-466
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• 2008

• Journal of Welding and Joining
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• v.25 no.5
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• pp.36-44
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• 2007

This paper is the first part of the study on the accuracy improvement of numerical analysis of steel welds. The aim of this paper is to raise the accuracy of thermal analysis results, such as the shape and size of the weld cross section and the hardness distribution in HAZ(Heat-Affected Zone). It is known that the factors affecting on the accuracy are thermal properties, metallurgical properties and welding heat source model. It was found that the arbitrary distributed heat source model should be used to predict practical weld cross section shape and size. Also, in order to improve the prediction accuracy of HAZ hardness distribution, it was essential to consider 2 CCT(Continuous Cooling Transformation) diagrams in calculating volume fraction of transformed phases. One is the peak temperature being around melting temperature. The other is the peak temperature being around metallurgical transformation temperature.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.718-723
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• 2016

The temperature changes are very important in improving the accuracy of the load forecasting during the summer. It is because the cooling load in summer contribute to the increasing of the load. This paper proposes a weekend load forecasting algorithm using the temperature change characteristic in a summer of Jeju. The days before and after weekends in Jeju, when the load curves are quite different from those of normal weekdays. The temperature change characteristic are obtained by using weekends peak load and high temperature data. And load forecasted based on the sensitivity between unit temperature changes and load variations. Load forecast data with better accuracy are obtained by using the proposed temperature changes than by using the ordinary daily peak load forecasting. The method can be used to reduce the error rate of load forecast.

• Progress in Superconductivity and Cryogenics
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• v.14 no.4
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• pp.46-49
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• 2012

The selection of the temperature sensor in the cryogenic system depends on the temperature range, shape and accuracy. The accuracy of the temperature sensor is essential to improve the reliability of experiment. We have developed the variable temperature cryostat using a two-stage cryocooler. In order to reduce heat load, thermal shield is installed at the first stage with MLI (Multiple layer insulation). We have also developed the sensor holder calibrating more than twenty sensors at the same time for saving time and money. The system can calibrate sensor at variable temperature by controlling electric heater. In this paper, we present design and fabrication of variable temperature cryostat and representative result of Cernox sensor calibration.