CAU Scholar's Space: Moon, Jin Woo

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Moon, Jin Woo (문진우)

공과대학 (건축학)

Research Area: 건축학

Tel 02-820-5209
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ResearcherID ORCiD Scopus Google Scholar ID ResearchGate

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Artificial neural network:12||Artificial Neural Network:11||인공신경망:10||Thermal Environment:8||온열환경:8||Data Center:5||데이터센터:5||Photosensor:4||Predicted Mean Vote:4||Clothing Insulation:4||Radiance:4||예측제어:4||Lighting energy:4||Sky conditions:4||예상평균온열감:4||인공지능:4||Optimal Control Algorithm:3||Metabolic rate:3||Lightshelf:3||Indoor Environment:3||Indoor Air Quality:3||Daylight coefficient approach:3||Daylight dimming control:3||최적 제어알고리즘:3||Correlation:3||착의량:3||Annual daylight simulation method:3||활동량:3||실내공기질:3||건물에너지:3||thermal comfort:3||Thermal comfort:3||Building Energy:3||Thermal Comfort:3||Target illuminance:3||환기시스템:3||Setback temperature:3||Prediction model:3||Predictive controls:2||Artificial Intelligence:2||Building energy:2||Control algorithm:2||Cooling system:2||Data center:2||Daylight:2||Daylight illuminance:2||Deep neural network:2||Energy cost:2||Energy efficiency:2||EnergyPlus:2||Indoor environment:2||Lighting energy savings:2||Machine Learning:2||Predictive Control:2||Predictive Controls:2||Predictive and adaptive controls:2||Research Trends:2||Sky:2||Sunmatching method:2||Ventilation System:2||Window ventilation system:2||artificial neural network (ANN):2||predictive controls:2||건물일체형태양전지:2||기계학습:2||실내환경:2||연구동향:2||열쾌적:2||예측모델:2||Energy Consumption:1||융복합 히트펌프 시스템:1||음환경:1||Air Conditioning System:1||Fuzzy:1||Fuzzy inference:1||Fuzzy logic:1||Gender Sensitivity:1||Ground source heat pump system:1||Heating Systems:1||Heating energy:1||Heating system:1||Human pose estimation:1||Hybrid Heat Pump System:1||Illumiance Sky conditions:1||Computational fluid dynamics:1||Computational algorithm:1||Indoor Temperature Prediction:1||Indoor air quality:1||Adaptive neurofuzzy inference system:1||Indoor temperature:1||Input Variables:1||Integral reset:1||Integrated neural network:1||Internet of Things:1||Internet of things:1||Lighting Environment:1||Comprehensive environments prediction:1||인공지능 제어:1||Coefficient of performance:1||입력변수:1||Machine learning:1||Market condition:1||Metabolic Rate:1||Coefficient of Variation Root Mean Square Error:1||Office:1||Office space:1||Openplan office:1||Optimal Control:1||Climate Zone:1||Optimal Control Variables:1||Optimal Controls:1||Optimal control algorithm:1||Optimal controls:1||Optimization:1||Optimum louver slat angle:1||Optimum system performance:1||PCW (Photochromic Window):1||PMV:1||PVintegrated shading device:1||Part load ratio:1||Particulate Matter:1||Peertopeer energy trading:1||Percent difference:1||Performance curve:1||Perimeter zone:1||Photoelectric dimming control:1||Chilled water mass flow control:1||Photosensorbased lighting control:1||Photovoltaic system:1||Pose classification:1||Calibration:1||Predicted Percentage Dissatisfied:1||Prediction Model:1||Buildingintegrated photovoltaics:1||적응형 제어알고리즘:1||전산유체역학:1||Predictive Mean Vote:1||Predictive Model:1||젠더 감수성:1||Predictive control:1||Accommodations:1||Building thermal environment:1||Refrigerant Flow Control:1||Refrigeration evaporation temperature setpoint:1||Adaptive neuro fuzzy inference system:1||Restoration period:1||Retraining:1||Rulebased Control:1||School Facility:1||School Indoor Air Quailty:1||Selective input connection:1||Semitransparent Window:1||Senser module:1||Sensor Module:1||Setback Temperature:1||Building space:1||Single board computer:1||창호:1||Sky condition:1||Building energy saving strategy:1||Sky patch:1||Smart Window:1||Smart windows:1||Solar Signage:1||창호형 환기시스템:1||Sunmatching:1||Supply air temperature setpoint:1||System components:1||System performance:1||Building System:1||Temperature control algorithm:1||Theoretical method:1||Building Integrated Photovoltaic:1||Bernoulli Principle:1||Thermal Quality:1||Bayesian optimization:1||Thermal conditioning:1||Thermal control algorithm:1||Thermal environment:1||Users’ preference:1||VRF Cooling System:1||VRF 냉방시스템:1||Variable refrigerant flow (VRF):1||Variable refrigerant flow heating system:1||창호환기시스템:1||Ventilation system:1||Visual comfort:1||Water Source Heat Pump System:1||Window:1||Window Ventilation System:1||최적 제어:1||Women:1||Women Policy:1||accommodations:1||artificial neural network:1||Adaptive control:1||ascending time:1||computational fluid dynamics:1||deep neural network:1||energy consumption:1||heating system:1||human joint estimation:1||indoor activity:1||life cycle cost (LCC):1||louver:1||metabolic rates:1||optimal setpoints of system variables:1||predicted mean vote (PMV):1||predictive control algorithm:1||최적제어:1||setback temperature:1||temperature controls:1||BIPV:1||variable refrigerant flow (VRF) cooling systems:1||ventilation:1||Artificial neural networks:1||최적제어변수:1||건축분야:1||건축연구:1||건축제도:1||공조시스템:1||광변색유리:1||규칙기반제어:1||평균 제곱근 오차 변동계수:1||기후대:1||난방시스템:1||냉매 유량 제어:1||냉방 에너지:1||냉방시스템:1||Artificial Intelligent:1||동적 착의량:1||딥러닝:1||딥러닝 신경망:1||미세먼지:1||반투명 태양전지 창호:1||베르누이원리:1||빛환경:1||사물인터넷:1||센서모듈:1||셋백온도:1||솔라사이니지:1||수열 히트펌프 시스템:1||숙박시설:1||스마트창호:1||시장현황:1||Artificial Intelligence Control System:1||실내온도 예측:1||학교 실내공기질:1||에너지소비:1||여성:1||여성정책:1||학교시설:1||Adaptive Control Algorithm:1||열환경:1||Cooling Energy:1||Cooling System:1||Cooling capacity:1||Cooling energy:1||염료감응형태양전지:1||Control performance:1||Cyber–Physical System:1||Cyberphysical system:1||DSSC:1||Control model and algorithm:1||Architectural Research:1||Acoustical Environment:1||Condenser fluid temperature setpoint:1||Condenser fluid pressure setpoint:1||Daylight dimming system:1||Daylight factor:1||Architectural Institution:1||Deep Learning:1||Deep Learning Neural Network:1||Architectural Field:1||Digital Twin:1||Dimming:1||Double skin envelope:1||Dyesensitized solar cell:1||Dynamic Clothing Insulation:1||Electricity production:1||Electrochromic windows:1||

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84, Heukseok-ro, Dongjak-gu, Seoul, Republic of Korea (06974)02-820-6194

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