• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.366-366
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• 2022

유역의 하천유량과 같은 수문 시계열을 모의 또는 예측하기 위한 수문 모델링에서 최근 기계 학습 방법을 활용한 연구가 활발하게 적용되고 있는 추세이다. 이러한 데이터 기반 모델링 접근법은 입출력 자료에서 관찰된 패턴을 학습하며, 특히, 장단기기억(Long Short-Term Memory, LSTM) 네트워크는 많은 연구에서 수문 시계열 예측에 대한 적용성이 검증되었으나, 장기간의 고품질 관측자료를 활용할 때 더 나은 예측성능을 보인다. 그러나 우리나라의 경우 장기간 관측된 고품질의 하천유량 자료를 확보하기 어려운 실정이다. 따라서 본 연구에서는 LSTM 네트워크의 학습 시 가용한 모든 유역의 자료를 통합하여 학습시켰을 때 하천유량 예측성능을 개선할 수 있는지 판단해보고자 하였다. 이를 위해, 우리나라 13개 댐 유역을 대상으로 대상 유역의 자료만을 학습한 모델의 예측성능과 모든 유역의 자료를 학습한 모델의 예측성능을 비교해 보았다. 학습은 2001년부터 2010년까지 기상자료(강우, 최저·최고·평균기온, 상대습도, 이슬점, 풍속, 잠재증발산)를 이용하였으며, 2011년부터 2020년에 대해 테스트 되었다. 다지점 통합학습을 통해 테스트 기간에 대해 예측된 각 유역의 일 하천유량의 KGE 중앙값이 0.74로 단일지점 학습을 통해 예측된 KGE(0.72)보다 다소 개선된 결과를 보여주었다. 다지점 통합학습이 하천유량 예측에 큰 개선을 달성하지는 못하였으며, 추가적인 가용 자료 확보와 LSTM 구성의 개선을 통해 추가적인 연구가 필요할 것으로 판단된다.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1373-1383
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• 2016

The wind energy industry and wind power generation have increased; consequently, the stable supply of the wind power has become an important issue. It is important to accurately predict the wind power with short-term basis in order to make a reliable planning for the power supply and demand of wind power. In this paper, we first analyzed the speed, power and the directions of the wind. The neural network and the time series models (ARMA, ARMAX, ARMA-GARCH, Holt Winters) for wind power generation forecasting were compared based on mean absolute error (MAE). For one to three hour-ahead forecast, ARMA-GARCH model was outperformed, and the neural network method showed a better performance in the six hour-ahead forecast.

• Fire Science and Engineering
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• v.33 no.3
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• pp.74-83
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• 2019

In the U.S., the pressurization of elevator shaft was developed in 1972 to allow vulnerable people, such as the elderly and weak who could not use escape stairs in case of fire, to evacuate. It is an advantage in terms of space saving by not using vertical ducts. This study drew the problem of the pressurization of elevator shaft based on the existing domestic patents and proposed improvements. The smoke control volume calculation method is proposed by using vertical modeling. Leakage gaps in elevator doors need to be reviewed through experimental data or actual data. The evacuation floor was divided, the openings in the elevator machine room were automatically closed to the fire signal and the relief damper was installed to improve the performance. The improved method functions as the smoke control damper supplying the air flow rather than maintaining the differential pressure. To increase reliability of the research results, the procedure was performed to verify by using Contam.

• Journal of Advanced Navigation Technology
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• v.22 no.3
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• pp.233-239
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• 2018

Since solar power generation is intermittent depending on weather conditions, it is necessary to predict the accurate generation amount of solar power to improve the efficiency and economical efficiency of solar power generation. This study proposes a short - term deep learning prediction model of solar power generation using meteorological data from Mokpo meteorological agency and generation data of Yeongam solar power plant. The meteorological agency forecasts weather factors such as temperature, precipitation, wind direction, wind speed, humidity, and cloudiness for three days. However, sunshine and solar radiation, the most important meteorological factors for forecasting solar power generation, are not predicted. The proposed model predicts solar radiation and solar radiation using forecast meteorological factors. The power generation was also forecasted by adding the forecasted solar and solar factors to the meteorological factors. The forecasted power generation of the proposed model is that the average RMSE and MAE of DNN are 0.177 and 0.095, and RNN is 0.116 and 0.067. Also, LSTM is the best result of 0.100 and 0.054. It is expected that this study will lead to better prediction results by combining various input.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.8
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• pp.1773-1779
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• 2015

Shore-to-sea visible light communication using color clustered multiple-input and multiple-output (MIMO) is presented. The proposed maritime visible light communication (MVLC) offers a low-cost, high-speed wireless link for shore-to-sea maritime communications. Each color cluster is comprised of 50 red, green and blue (RGB) light emitting diodes (LEDs) and is modulated using on-off-keying (OOK). Selection combining is performed at the receiver, producing diversity effect within that color cluster. In this paper, we employ sea states (wave height, wind speed, etc.) data from both Pierson-Moskowitz and JONSWAP spectrum models under atmospheric turbulence conditions. Based on the simulation model, the maritime link quality is analysed in terms of coverage distance and bit error rate performance. The results show that the proposed system provides an efficient MVLC, while satisfying International Association of Lighthouse Authorities (IALA) requirements for maritime buoyage system and also offering sufficient illumination from high power LEDs.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1187-1198
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• 2021

Sea wind isrecently drawing attraction as one of the sources of renewable energy. Thisstudy describes a new method to produce a 10 m resolution sea wind field using Sentinel-1 images and low-resolution NWP (Numerical Weather Prediction) data with artificial intelligence technique. The experiment for the South East coast in Korea, 2015-2020,showed a 40% decreased MAE (Mean Absolute Error) than the generic CMOD (C-band Model) function, and the CC (correlation coefficient) of our method was 0.901 and 0.826, respectively, for the U and V wind components. We created 10m resolution sea wind maps for the study area, which showed a typical trend of wind distribution and a spatially detailed wind pattern as well. The proposed method can be applied to surveying for wind power and information service for coastal disaster prevention and leisure activities.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.551-556
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• 2018

In recent years, drones have been used to measure aircraft flights data and weather information. Related applications include the measure for low-altitude atmospheric data, the measure for atmospheric fine dust, and the measure for air pollution. However, the mounting position of the atmospheric measurement sensor should be mounted by considering the effects of propeller flow, the EMI effects, and the changes in the weight of the drone. Among these, the upper flow of the propeller affects the wind speed and direction, so the optimal position should be selected. This study deals with the proper height of the atmospheric data measurement sensor. Through the flow analysis, we study the flow characteristics of around a drone and suggest the proper sensor mounting height.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.50-61
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• 2022

Snow, rain, fog, and particulate matter interfere with the vehicle driver's vision, which causes a non-secure safety distance and an increase in speed deviation, causing repetitive large-scale traffic accidents. This study developed a road environment sensor capable of measuring 11 types of fog, snow, rain, temperature, humidity, direction of wind, speed of wind, Insolation, atmospheric pressure, fine particles, rainfall, etc. and compared the visibility measured by the infrared signal value of the development sensor. The relationship between the existing fog visibility sensor and the development sensor measurement was derived from data measured at a visibility of 500m or less that directly affects road safety.

• The Journal of the Acoustical Society of Korea
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• v.39 no.6
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• pp.606-614
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• 2020

In this paper, we analyze the influences of ship traffic and marine weather information on underwater ambient noise. Ambient noise is an important environmental factor that greatly affects the detection performance of underwater sonar systems. In order to implement an automated system such as prediction of detection performance using artificial intelligence technology, which has been recently studied, it is necessary to obtain and analyze major data related to these. The main sources of ambient noise have various causes. In the case of sonar systems operating in offshore seas, the detection performance is greatly affected by the noise caused by ship traffic and marine weather. Therefore, in this paper, the impact of each data was analyzed using the measurement results of ambient noise obtained in coastal area of the East Sea of Korea, and public data of nearby ship traffic and ocean weather information. As a result, it was observed that the underwater ambient noise was highly correlated with the change of the ship's traffic volume, and that marine environment factors such as wind speed, wave height, and rainfall had an effect on a specific frequency band.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1739-1749
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• 2018

We propose a marine observation system using existing light buoys to observe various marine information of marine locations. Our proposed ocean observation system is composed of the existing standard light buoy type and can be easily connected to the light buoy. The proposed marine observation system measures the mean wave height, maximum wave height, mean wave height and water temperature measured in the ocean. Besides, it can measure the air pressure, temperature, wind speed and wind speed in real time. In order to measure important peaks in marine observations, 2200 peak data are collected for 10 minutes, and the collected data are subjected to spectral analysis to extract significant wave and wave period data. The developed system removes the noise by using the filter because the marine observation system attaches to the light buoy. We compare and analyze the measurement data of the existing proven floating marine observation system and the standard equivalent system developed. Also, it is proved that the data of the standard type backbone ocean observation system developed through the comparative experiment is similar to that of the existing ocean observation system.