CAU Scholar's Space: Kim, Sahm Yong

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Kim, Sahm Yong (김삼용)

대학원 (통계데이터사이언스학과)

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Tel 02-820-5225
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ARIMA:7||HoltWinters:6||GARCH:4||ARIMAX:4||시계열 모형:4||ARGARCH:4||internet traffic:4||MAPE:4||GARCH 모형:4||XGBoost:3||forecasting:3||GARCH model:3||Random Forest:3||machine learning:3||FARIMA:3||LSTM:3||time series:3||Outliers:2||HoltWinters 모형:2||weather variables:2||ARCH model:2||Fractional Seasonal ARIMA:2||Internet traffic:2||daily peak load:2||계절형 ARIMA 모형:2||TBATS:2||트래픽:2||Kmeans clustering:2||KOSPI:2||KOSPI data:2||random forest:2||electricity demand forecasting:2||로버스트 추정:2||다변량 시계열 모형:2||ARGARCH 모형:2||seasonal ARIMA:2||Timeseries clustering:2||비대칭성:2||VAR model:2||MLE:2||GRU:2||예측:2||Robust estimation:2||solar radiation:2||ANN:2||time series clustering:2||time series model:2||Seasonal ARGARCH:2||Seasonal ARIMA model:2||장기기억:2||KOSPI 자료:1||KTX Passenger:1||KTX여객수:1||MCMC:1||MCMC:Volatility:1||MLP:1||Martingale:1||NNAR:1||Network Traffic:1||Nonlinear time series:1||PGARCH model:1||PM10:1||Peak load demand forecasting:1||Precipitation:1||Predictive models:1||Quasi likelihood estimator:1||QuasiLikelihood Function:1||Quasilikelihood estimation:1||Random Coefficient Autoregressive model:1||Recurrent neural networks:1||RegARGARCH model:1||RegARGARCH모형:1||RegARIMA:1||RegARIMA 모형:1||RegARMA model:1||RegARMA 모형:1||Renewable energy sources:1||Residential electricity demand:1||Robust estimators:1||SV 모형:1||SVM:1||Seasonal FARIMA:1||Smart grid:1||Smart meter data:1||Solar energy:1||Solar radiation:1||Solar radiation forecasting:1||TBATS model:1||Taylor's HoltWinters model:1||Taylor's HoltWinters 모형:1||The collegeentrance processes:1||ThresholdARCH:1||Time Series Models:1||Time Series models:1||Time series:1||Time series models:1||Timeseries forecasting:1||Traffic:1||VARX:1||Weather variables:1||Wind speed:1||XGB:1||adjusted HoltWinters:1||air passengers.:1||airdemand.:1||binary random power:1||categorical boosting (CatBoost):1||charging demand:1||charging stations:1||combined forecasting:1||combining forecasting:1||convolutional neural network (CNN):1||cooperation of both academia and industry:1||double seasonal HoltWinters model:1||doubly robustified estimating function:1||dynamic conditional correlation:1||dynamic time warping:1||electric load forecasting:1||electric vehicle:1||electricity demand:1||electricity load:1||epsilonsupport vector regression (epsilonSVR):1||estimation:1||explosive AR(1):1||extraterrestrial radiation:1||factors analysis:1||forecasitng:1||forecasting.:1||frost prediction:1||generalized least squares:1||household electric usage forecasting:1||hybrid model (CNNCatBoost):1||interdisciplinary property:1||international freight:1||iterative least squares(ILS):1||likelihood method:1||long memory:1||longmemory:1||maximum:1||mean absolute percentage error (MAPE):1||multiple regression:1||network traffic:1||neural network:1||nonsymmetry:1||outlier detection:1||peak load:1||performance evaluation:1||price duration:1||probability density function:1||pseudo maximum likelihood(PML).:1||regression:1||regression analysis:1||robust:1||root mean square error (RMSE):1||seasonal AIRMAX GARCH:1||seasonal VAR model:1||seasonal autoregressive integrated moving average (ARIMA):1||seasonal autoregressivegeneralized autoregressive conditional heteroscedasticity (ARGARCH):1||seasonality:1||shocks impact curve:1||simple RNN:1||smart grid:1||solar irradiance:1||solar power:1||solar radiation forecasting:1||special days effect:1||statistical test:1||stock indexes:1||time series cross validation:1||timeVarying correlation:1||tourism demand:1||traffic data:1||volatility:1||weather variable:1||wind power:1||wind power forecasting:1||가격 거래 시간:1||결합예측:1||계절성:1||계절형 다변량 시계열 모형:1||관광수요:1||국제항공여객:1||국제항공화물:1||금융공학:1||기계학습:1||기상변수:1||난방지수:1||냉방지수:1||로버스트 통계량:1||머신러닝:1||멱변환 GARCH 모형:1||멱변환 TARCH 모형:1||모의실험:1||미세먼지 예측:1||비선형 ARCH 모형:1||산학협동:1||스마트 그리드:1||시계열:1||시계열 군집분석:1||오차수정모형:1||요인분석:1||이분산성 검정통계량:1||이분산성 모형:1||이상치:1||이상치 탐지:1||이항멱변환 분계점 일반 자기회귀 이분산 모형:1||인터넷 트래픽:1||일별 최대전력수요:1||일별최대전력:1||일사량:1||일사량 예측:1||입학전형:1||전기 자동차:1||전력수요:1||전력수요예측:1||주가지수:1||주택용 전력사용량 예측:1||중기예보:1||최대가능도법:1||최대전력치:1||충격 함수 곡선:1||충전 전력량:1||통계적 검정:1||트래픽 자료:1||특수일 효과:1||풍력 데이터:1||학업성취도:1||학제간 협동:1||항공수요:1||항공수요.:1||확률 밀도 함수:1||ACD model:1||회귀분석:1||ACD 모형:1||AMI data:1||AMI 데이터:1||ARGARCH model:1||ARCH:1||ARCH errors:1||ARCH모형:1||ARIMA model:1||ARIMA 모형:1||ARMA GARCH:1||ARMAX:1||Akaike information criterion (AIC):1||Artificial Neural Network:1||Asymmetric ARCH:1||Asymptotic normality:1||Asymptotic relative efficiency.:1||BoxCox transformation:1||BoxCox 변환:1||Bps:1||C22:1||CDD:1||CNN:1||CatBoost:1||Charging power:1||Climate change:1||Copula:1||DSHW:1||Deep learning:1||E43:1||E44:1||ECM model:1||EV:1||Electricity Demand.:1||Estimating Function:1||Estimating functions:1||Financial engineering:1||Forecast:1||Forecasting:1||Fractional ARIMA:1||Fractional ARIMAGARCH:1||GPTTGARCH model:1||GRACH model:1||GRACH 모형:1||HDD:1||Holt Winters:1||HoltWinters model:1||Huber's function:1||Institutional building:1||International passengers:1||

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