• Title/Summary/Keyword: Prediction Modeling

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Multi-task Learning Based Tropical Cyclone Intensity Monitoring and Forecasting through Fusion of Geostationary Satellite Data and Numerical Forecasting Model Output (정지궤도 기상위성 및 수치예보모델 융합을 통한 Multi-task Learning 기반 태풍 강도 실시간 추정 및 예측)

  • Lee, Juhyun;Yoo, Cheolhee;Im, Jungho;Shin, Yeji;Cho, Dongjin
    • Korean Journal of Remote Sensing
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    • v.36 no.5_3
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    • pp.1037-1051
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    • 2020
  • The accurate monitoring and forecasting of the intensity of tropical cyclones (TCs) are able to effectively reduce the overall costs of disaster management. In this study, we proposed a multi-task learning (MTL) based deep learning model for real-time TC intensity estimation and forecasting with the lead time of 6-12 hours following the event, based on the fusion of geostationary satellite images and numerical forecast model output. A total of 142 TCs which developed in the Northwest Pacific from 2011 to 2016 were used in this study. The Communications system, the Ocean and Meteorological Satellite (COMS) Meteorological Imager (MI) data were used to extract the images of typhoons, and the Climate Forecast System version 2 (CFSv2) provided by the National Center of Environmental Prediction (NCEP) was employed to extract air and ocean forecasting data. This study suggested two schemes with different input variables to the MTL models. Scheme 1 used only satellite-based input data while scheme 2 used both satellite images and numerical forecast modeling. As a result of real-time TC intensity estimation, Both schemes exhibited similar performance. For TC intensity forecasting with the lead time of 6 and 12 hours, scheme 2 improved the performance by 13% and 16%, respectively, in terms of the root mean squared error (RMSE) when compared to scheme 1. Relative root mean squared errors(rRMSE) for most intensity levels were lessthan 30%. The lower mean absolute error (MAE) and RMSE were found for the lower intensity levels of TCs. In the test results of the typhoon HALONG in 2014, scheme 1 tended to overestimate the intensity by about 20 kts at the early development stage. Scheme 2 slightly reduced the error, resulting in an overestimation by about 5 kts. The MTL models reduced the computational cost about 300% when compared to the single-tasking model, which suggested the feasibility of the rapid production of TC intensity forecasts.

1-month Prediction on Rice Harvest Date in South Korea Based on Dynamically Downscaled Temperature (역학적 규모축소 기온을 이용한 남한지역 벼 수확일 1개월 예측)

  • Jina Hur;Eun-Soon Im;Subin Ha;Yong-Seok Kim;Eung-Sup Kim;Joonlee Lee;Sera Jo;Kyo-Moon Shim;Min-Gu Kang
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.25 no.4
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    • pp.267-275
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    • 2023
  • This study predicted rice harvest date in South Korea using 11-year (2012-2022) hindcasts based on dynamically downscaled 2m air temperature at subseasonal (1-month lead) timescale. To obtain high (5 km) resolution meteorological information over South Korea, global prediction obtained from the NOAA Climate Forecast System (CFSv2) is dynamically downscaled using the Weather Research and Forecasting (WRF) double-nested modeling system. To estimate rice harvest date, the growing degree days (GDD) is used, which accumulated the daily temperature from the seeding date (1 Jan.) to the reference temperature (1400℃ + 55 days) for harvest. In terms of the maximum (minimum) temperatures, the hindcasts tends to have a cold bias of about 1. 2℃ (0. 1℃) for the rice growth period (May to October) compared to the observation. The harvest date derived from hindcasts (DOY 289) well simulates one from observation (DOY 280), despite a margin of 9 days. The study shows the possibility of obtaining the detailed predictive information for rice harvest date over South Korea based on the dynamical downscaling method.

A Comparative Study on the Improvement of Curriculum in the Junior College for the Industrial Design Major (2년제 대학 산업디자인전공의 교육과정 개선방안에 관한 비교연구)

  • 강사임
    • Archives of design research
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    • v.13 no.1
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    • pp.209-218
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    • 2000
  • The purpose of this study was to improve the curriculum for industrial design department in the junior colleges. In order to achieve the purpose, two methodologies were carried out. First is job analysis of the industrial designers who have worked in the small & medium manufacturing companies, second is survey for the opinions of professors in the junior colleges. Some results were as follows: 1. The period of junior college for industrial designers is 2 years according to present. But selectively 1 year of advanced course can be established. 2. The practice subjects same as computational formative techniques needed to product development have to be increased. In addition kinds of selection subjects same as foreign language, manufacturing process, new product information and consumer behavior investigation have to be extended. 3. The next subjects need to adjust the title, contents and hours. (1) The need of 3.D related subjects same as computer modeling, computer rendering, 3.D modeling was high. The use of computer is required to design presentation subjects. (2)The need of advertising and sale related subjects same as printing, merchandise, package, typography, photography was low, the need of presentation techniques of new product development was high. (3) The need of field practice, special lecture on practice and reading original texts related subjects was same as at present, but these are not attached importance to form. As the designers feel keenly the necessity of using foreign language, the need of language subject was high.

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Sensitivity of Simulated Water Temperature to Vertical Mixing Scheme and Water Turbidity in the Yellow Sea (수직 혼합 모수화 기법과 탁도에 따른 황해 수온 민감도 실험)

  • Kwak, Myeong-Taek;Seo, Gwang-Ho;Choi, Byoung-Ju;Kim, Chang-Sin;Cho, Yang-Ki
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.18 no.3
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    • pp.111-121
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    • 2013
  • Accurate prediction of sea water temperature has been emphasized to make precise local weather forecast and to understand change of ecosystem. The Yellow Sea, which has turbid water and strong tidal current, is an unique shallow marginal sea. It is essential to include the effects of the turbidity and the strong tidal mixing for the realistic simulation of temperature distribution in the Yellow Sea. Evaluation of ocean circulation model response to vertical mixing scheme and turbidity is primary objective of this study. Three-dimensional ocean circulation model(Regional Ocean Modeling System) was used to perform numerical simulations. Mellor- Yamada level 2.5 closure (M-Y) and K-Profile Parameterization (KPP) scheme were selected for vertical mixing parameterization in this study. Effect of Jerlov water type 1, 3 and 5 was also evaluated. The simulated temperature distribution was compared with the observed data by National Fisheries Research and Development Institute to estimate model's response to turbidity and vertical mixing schemes in the Yellow Sea. Simulations with M-Y vertical mixing scheme produced relatively stronger vertical mixing and warmer bottom temperature than the observation. KPP scheme produced weaker vertical mixing and did not well reproduce tidal mixing front along the coast. However, KPP scheme keeps bottom temperature closer to the observation. Consequently, numerical ocean circulation simulations with M-Y vertical mixing scheme tends to produce well mixed vertical temperature structure and that with KPP vertical mixing scheme tends to make stratified vertical temperature structure. When Jerlov water type is higher, sea surface temperature is high and sea bottom temperature is low because downward shortwave radiation is almost absorbed near the sea surface.

Simulation and model validation of Biomass Fast Pyrolysis in a fluidized bed reactor using CFD (전산유체역학(CFD)을 이용한 유동층반응기 내부의 목질계 바이오매스 급속 열분해 모델 비교 및 검증)

  • Ju, Young Min;Euh, Seung Hee;Oh, Kwang cheol;Lee, Kang Yol;Lee, Beom Goo;Kim, Dae Hyun
    • Journal of Energy Engineering
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    • v.24 no.4
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    • pp.200-210
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    • 2015
  • The modeling for fast pyrolysis of biomass in fluidized bed reactor has been developed for accurate prediction of bio-oil and gas products and for yield improvement. The purpose of this study is to analyze and to compare the CFD(Computational Fluid Dynamics) simulation results with the experimental data from the CFD simulation results with the experimental data from the reference(Mellin et al., 2014) for gas products generated during fast pyrolysis of biomass in fluidized bed reactor. CFD(ANSYS FLUENT v.15.0) was used for the simulation. Complex pyrolysis reaction scheme of biomass subcomponents was applied for the simulation of pyrolysis reaction. This pyrolysis reaction scheme was included reaction of cellulose, hemicellulose, lignin in detail, gas products obtained from pyrolysis were mainly $CO_2$, CO, $CH_4$, $H_2$, $C_2H_4$. The deviation between the simulation results from this study and experimental data from the reference was calculated about 3.7%p, 4.6%p, 3.9%p for $CH_4$, $H_2$, $C_2H_4$ respectively, whereas 9.6%p and 6.7%p for $CO_2$ and CO which are relatively high. Through this study, it is possible to predict gas products accurately by using CFD simulation approach. Moreover, this modeling approach should be developed to predict fluidized bed reactor performance and other gas product yields.

Bias Correction for GCM Long-term Prediction using Nonstationary Quantile Mapping (비정상성 분위사상법을 이용한 GCM 장기예측 편차보정)

  • Moon, Soojin;Kim, Jungjoong;Kang, Boosik
    • Journal of Korea Water Resources Association
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    • v.46 no.8
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    • pp.833-842
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    • 2013
  • The quantile mapping is utilized to reproduce reliable GCM(Global Climate Model) data by correct systematic biases included in the original data set. This scheme, in general, projects the Cumulative Distribution Function (CDF) of the underlying data set into the target CDF assuming that parameters of target distribution function is stationary. Therefore, the application of stationary quantile mapping for nonstationary long-term time series data of future precipitation scenario computed by GCM can show biased projection. In this research the Nonstationary Quantile Mapping (NSQM) scheme was suggested for bias correction of nonstationary long-term time series data. The proposed scheme uses the statistical parameters with nonstationary long-term trends. The Gamma distribution was assumed for the object and target probability distribution. As the climate change scenario, the 20C3M(baseline scenario) and SRES A2 scenario (projection scenario) of CGCM3.1/T63 model from CCCma (Canadian Centre for Climate modeling and analysis) were utilized. The precipitation data were collected from 10 rain gauge stations in the Han-river basin. In order to consider seasonal characteristics, the study was performed separately for the flood (June~October) and nonflood (November~May) seasons. The periods for baseline and projection scenario were set as 1973~2000 and 2011~2100, respectively. This study evaluated the performance of NSQM by experimenting various ways of setting parameters of target distribution. The projection scenarios were shown for 3 different periods of FF scenario (Foreseeable Future Scenario, 2011~2040 yr), MF scenario (Mid-term Future Scenario, 2041~2070 yr), LF scenario (Long-term Future Scenario, 2071~2100 yr). The trend test for the annual precipitation projection using NSQM shows 330.1 mm (25.2%), 564.5 mm (43.1%), and 634.3 mm (48.5%) increase for FF, MF, and LF scenarios, respectively. The application of stationary scheme shows overestimated projection for FF scenario and underestimated projection for LF scenario. This problem could be improved by applying nonstationary quantile mapping.

Water Digital Twin for High-tech Electronics Industrial Wastewater Treatment System (I): e-ASM Development and Digital Simulation Implementation (첨단 전자산업 폐수처리시설의 Water Digital Twin(I): e-ASM 모델 개발과 Digital Simulation 구현)

  • Shim, Yerim;Lee, Nahui;Jeong, Chanhyeok;Heo, SungKu;Kim, SangYoon;Nam, KiJeon;Yoo, ChangKyoo
    • Clean Technology
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    • v.28 no.1
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    • pp.63-78
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    • 2022
  • Electronics industrial wastewater treatment facilities release organic wastewaters containing high concentrations of organic pollutants and more than 20 toxic non-biodegradable pollutants. One of the major challenges of the fourth industrial revolution era for the electronics industry is how to treat electronics industrial wastewater efficiently. Therefore, it is necessary to develop an electronics industrial wastewater modeling technique that can evaluate the removal efficiency of organic pollutants, such as chemical oxygen demand (COD), total nitrogen (TN), total phosphorous (TP), and tetramethylammonium hydroxide (TMAH), by digital twinning an electronics industrial organic wastewater treatment facility in a cyber physical system (CPS). In this study, an electronics industrial wastewater activated sludge model (e-ASM) was developed based on the theoretical reaction rates for the removal mechanisms of electronics industrial wastewater considering the growth and decay of micro-organisms. The developed e-ASM can model complex biological removal mechanisms, such as the inhibition of nitrification micro-organisms by non-biodegradable organic pollutants including TMAH, as well as the oxidation, nitrification, and denitrification processes. The proposed e-ASM can be implemented as a Water Digital Twin for real electronics industrial wastewater treatment systems and be utilized for process modeling, effluent quality prediction, process selection, and design efficiency across varying influent characteristics on a CPS.

Impact Assessment of Agricultural Reservoir on Streamflow Simulation Using Semi-distributed Hydrologic Model (준분포형 모형을 이용한 농업용 저수지가 안성천 유역의 유출모의에 미치는 영향 평가)

  • Kim, Bo Kyung;Kim, Byung Sik;Kwon, Hyun Han
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.1B
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    • pp.11-22
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    • 2009
  • Long-term rainfall-runoff modeling is a key element in the Earth's hydrological cycle, and associated with many different aspects such as dam design, drought management, river management flow, reservoir management for water supply, water right permission or coordinate, water quality prediction. In this regard, hydrologists have used the hydrologic models for design criteria, water resources assessment, planning and management as a main tool. Most of rainfall-runoff studies, however, were not carefully performed in terms of considering reservoir effects. In particular, the downstream where is severely affected by reservoir was poorly dealt in modeling rainfall-runoff process. Moreover, the effects can considerably affect overall the rainfallrunoff process. An objective of this study, thus, is to evaluate the impact of reservoir operation on rainfall-runoff process. The proposed approach is applied to Anseong watershed, where is in a mixed rural/urban setting of the area and in Korea, and has been experienced by flood damage due to heavy rainfall. It has been greatly paid attention to the agricultural reservoirs in terms of flood protection in Korea. To further investigate the reservoir effects, a comprehensive assessment for the results are discussed. Results of simulations that included reservoir in the model showed the effect of storage appeared in spring and autumn when rainfall was not concentrated. In periods of heavy rainfall, however, downstream runoff increased in simulations that do not consider reservoir factor. Flow duration curve showed that changes in streamflow depending upon the presence or absence of reservoir factor were particularly noticeable in ninety-five day flow and low flow.

Estimation of Internal Motion for Quantitative Improvement of Lung Tumor in Small Animal (소동물 폐종양의 정량적 개선을 위한 내부 움직임 평가)

  • Yu, Jung-Woo;Woo, Sang-Keun;Lee, Yong-Jin;Kim, Kyeong-Min;Kim, Jin-Su;Lee, Kyo-Chul;Park, Sang-Jun;Yu, Ran-Ji;Kang, Joo-Hyun;Ji, Young-Hoon;Chung, Yong-Hyun;Kim, Byung-Il;Lim, Sang-Moo
    • Progress in Medical Physics
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    • v.22 no.3
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    • pp.140-147
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    • 2011
  • The purpose of this study was to estimate internal motion using molecular sieve for quantitative improvement of lung tumor and to localize lung tumor in the small animal PET image by evaluated data. Internal motion has been demonstrated in small animal lung region by molecular sieve contained radioactive substance. Molecular sieve for internal lung motion target was contained approximately 37 kBq Cu-64. The small animal PET images were obtained from Siemens Inveon scanner using external trigger system (BioVet). SD-Rat PET images were obtained at 60 min post injection of FDG 37 MBq/0.2 mL via tail vein for 20 min. Each line of response in the list-mode data was converted to sinogram gated frames (2~16 bin) by trigger signal obtained from BioVet. The sinogram data was reconstructed using OSEM 2D with 4 iterations. PET images were evaluated with count, SNR, FWHM from ROI drawn in the target region for quantitative tumor analysis. The size of molecular sieve motion target was $1.59{\times}2.50mm$. The reference motion target FWHM of vertical and horizontal was 2.91 mm and 1.43 mm, respectively. The vertical FWHM of static, 4 bin and 8 bin was 3.90 mm, 3.74 mm, and 3.16 mm, respectively. The horizontal FWHM of static, 4 bin and 8 bin was 2.21 mm, 2.06 mm, and 1.60 mm, respectively. Count of static, 4 bin, 8 bin, 12 bin and 16 bin was 4.10, 4.83, 5.59, 5.38, and 5.31, respectively. The SNR of static, 4 bin, 8 bin, 12 bin and 16 bin was 4.18, 4.05, 4.22, 3.89, and 3.58, respectively. The FWHM were improved in accordance with gate number increase. The count and SNR were not proportionately improve with gate number, but shown the highest value in specific bin number. We measured the optimal gate number what minimize the SNR loss and gain improved count when imaging lung tumor in small animal. The internal motion estimation provide localized tumor image and will be a useful method for organ motion prediction modeling without external motion monitoring system.

Implementation Strategy of Global Framework for Climate Service through Global Initiatives in AgroMeteorology for Agriculture and Food Security Sector (선도적 농림기상 국제협력을 통한 농업과 식량안보분야 전지구기후 서비스체계 구축 전략)

  • Lee, Byong-Lyol;Rossi, Federica;Motha, Raymond;Stefanski, Robert
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.15 no.2
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    • pp.109-117
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    • 2013
  • The Global Framework on Climate Services (GFCS) will guide the development of climate services that link science-based climate information and predictions with climate-risk management and adaptation to climate change. GFCS structure is made up of 5 pillars; Observations/Monitoring (OBS), Research/ Modeling/ Prediction (RES), Climate Services Information System (CSIS) and User Interface Platform (UIP) which are all supplemented with Capacity Development (CD). Corresponding to each GFCS pillar, the Commission for Agricultural Meteorology (CAgM) has been proposing "Global Initiatives in AgroMeteorology" (GIAM) in order to facilitate GFCS implementation scheme from the perspective of AgroMeteorology - Global AgroMeteorological Outlook System (GAMOS) for OBS, Global AgroMeteorological Pilot Projects (GAMPP) for RES, Global Federation of AgroMeteorological Society (GFAMS) for UIP/RES, WAMIS next phase for CSIS/UIP, and Global Centers of Research and Excellence in AgroMeteorology (GCREAM) for CD, through which next generation experts will be brought up as virtuous cycle for human resource procurements. The World AgroMeteorological Information Service (WAMIS) is a dedicated web server in which agrometeorological bulletins and advisories from members are placed. CAgM is about to extend its service into a Grid portal to share computer resources, information and human resources with user communities as a part of GFCS. To facilitate ICT resources sharing, a specialized or dedicated Data Center or Production Center (DCPC) of WMO Information System for WAMIS is under implementation by Korea Meteorological Administration. CAgM will provide land surface information to support LDAS (Land Data Assimilation System) of next generation Earth System as an information provider. The International Society for Agricultural Meteorology (INSAM) is an Internet market place for agrometeorologists. In an effort to strengthen INSAM as UIP for research community in AgroMeteorology, it was proposed by CAgM to establish Global Federation of AgroMeteorological Society (GFAMS). CAgM will try to encourage the next generation agrometeorological experts through Global Center of Excellence in Research and Education in AgroMeteorology (GCREAM) including graduate programmes under the framework of GENRI as a governing hub of Global Initiatives in AgroMeteorology (GIAM of CAgM). It would be coordinated under the framework of GENRI as a governing hub for all global initiatives such as GFAMS, GAMPP, GAPON including WAMIS II, primarily targeting on GFCS implementations.