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Taehoon Hong

Taehoon Hong

D-Index & Metrics

Engineering and Technology

D-Index
57
Citations
10354
World Ranking
2705
National Ranking
50

Overview

Taehoon Hong is affiliated with Yonsei University in South Korea and conducts research in the field of Engineering. Their main area of focus includes Building and Construction, Electrical and Electronic Engineering, Civil and Structural Engineering, Environmental Engineering, and Social Psychology.

The scholar's research spans multiple topics related to building energy, infrastructure, and environmental management. Key topics of study include:

  • Building Energy and Comfort Optimization
  • Noise Effects and Management
  • Infrastructure Maintenance and Monitoring
  • BIM and Construction Integration
  • Sustainable Building Design and Assessment
  • Smart Grid Energy Management
  • Color perception and design

Frequent publication venues where Taehoon Hong has contributed include:

  • Building and Environment
  • Energy and Buildings
  • Renewable and Sustainable Energy Reviews
  • Automation in Construction
  • Journal of Management in Engineering

Notable recent papers authored or co-authored by Taehoon Hong cover multiple aspects of energy conservation, indoor environmental quality, and the impact of environmental factors on occupants. These include:

  • "A systematic review of the smart energy conservation system: From smart homes to sustainable smart cities," 2021, Renewable and Sustainable Energy Reviews
  • "Psychological and physiological effects of a green wall on occupants: A cross-over study in virtual reality," 2021, Building and Environment
  • "A psychophysiological effect of indoor thermal condition on college students' learning performance through EEG measurement," 2020, Building and Environment
  • "Changes in energy consumption according to building use type under COVID-19 pandemic in South Korea," 2021, Renewable and Sustainable Energy Reviews
  • "Predicting industrial building energy consumption with statistical and machine-learning models informed by physical system parameters," 2022, Renewable and Sustainable Energy Reviews

Taehoon Hong has collaborated extensively with other researchers. Frequent co-authors include:

  • Hakpyeong Kim
  • Jongbaek An
  • Hyuna Kang
  • Dong-Eun Lee
  • Seunghoon Jung

Best Publications

  • A systematic review of the smart energy conservation system: From smart homes to sustainable smart cities

    Hakpyeong Kim;Heeju Choi;Hyuna Kang;Jongbaek An

  • Effect of project characteristics on project performance in construction projects based on structural equation model

    KyuMan Cho;TaeHoon Hong;ChangTaek Hyun

  • A review on sustainable construction management strategies for monitoring, diagnosing, and retrofitting the building's dynamic energy performance: Focused on the operation and maintenance phase

    Taehoon Hong;Choongwan Koo;Jimin Kim;Minhyun Lee

  • Development of a method for estimating the rooftop solar photovoltaic (PV) potential by analyzing the available rooftop area using Hillshade analysis

    Taehoon Hong;Minhyun Lee;Choongwan Koo;Choongwan Koo;Kwangbok Jeong

  • Assessment Model for Energy Consumption and Greenhouse Gas Emissions during Building Construction

    Taehoon Hong;ChangYoon Ji;MinHo Jang;HyoSeon Park

  • Analysis of South Korea’s economic growth, carbon dioxide emission, and energy consumption using the Markov switching model

    JaeHyun Park;TaeHoon Hong

  • A CBR-based hybrid model for predicting a construction duration and cost based on project characteristics in multi-family housing projects

    ChoongWan KooC. Koo;TaeHoon HongT. Hong;ChangTaek HyunC. Hyun;KyoJin KooK. Koo

  • LCC and LCCO2 analysis of green roofs in elementary schools with energy saving measures

    TaeHoon Hong;JiMin Kim;ChoongWan Koo

  • Development of a new energy benchmark for improving the operational rating system of office buildings using various data-mining techniques

    Hyo Seon Park;Minhyun Lee;Hyuna Kang;Taehoon Hong

  • An estimation model for determining the annual energy cost budget in educational facilities using SARIMA (seasonal autoregressive integrated moving average) and ANN (artificial neural network)

    Kwangbok Jeong;Choongwan Koo;Taehoon Hong

  • A psychophysiological effect of indoor thermal condition on college students’ learning performance through EEG measurement

    Hakpyeong Kim;Taehoon Hong;Jimin Kim;Seungkeun Yeom

  • A GIS (geographic information system)-based optimization model for estimating the electricity generation of the rooftop PV (photovoltaic) system

    Taehoon Hong;Choongwan Koo;Joonho Park;Hyo Seon Park

  • Cost and CO2 Emission Optimization of Steel Reinforced Concrete Columns in High-Rise Buildings

    Hyo Seon Park;Bongkeun Kwon;Yunah Shin;Yousok Kim

  • Occupant responses on satisfaction with window size in physical and virtual built environments

    Taehoon Hong;Minhyun Lee;Seungkeun Yeom;Kwangbok Jeong

  • Determining the Peer-to-Peer electricity trading price and strategy for energy prosumers and consumers within a microgrid

    Jongbaek An;Minhyun Lee;Seungkeun Yeom;Taehoon Hong

  • Changes in energy consumption according to building use type under COVID-19 pandemic in South Korea

    Hyuna Kang;Jongbaek An;Hakpyeong Kim;Changyoon Ji

  • An optimization model for selecting the optimal green systems by considering the thermal comfort and energy consumption

    Jimin Kim;Taehoon Hong;Jaemin Jeong;Choongwan Koo;Choongwan Koo

  • Economic and environmental evaluation model for selecting the optimum design of green roof systems in elementary schools

    Jimin Kim;Taehoon Hong;Choong Wan Koo

  • Integrated model for assessing the cost and CO2 emission (IMACC) for sustainable structural design in ready-mix concrete

    Taehoon Hong;Changyoon Ji;Hyoseon Park

  • Development of a new energy efficiency rating system for existing residential buildings

    Choongwan Koo;Taehoon Hong;Minhyun Lee;Hyo Seon Park

  • An estimation model for the heating and cooling demand of a residential building with a different envelope design using the finite element method

    Choongwan Koo;Sungki Park;Taehoon Hong;Hyo Seon Park

  • The development of a construction cost prediction model with improved prediction capacity using the advanced CBR approach

    ChoongWan Koo;TaeHoon Hong;ChangTaek Hyun

Frequent Co-Authors

Choongwan Koo
Choongwan Koo Incheon National University
Minhyun Lee
Minhyun Lee Hong Kong Polytechnic University
Hyo Seon Park
Hyo Seon Park Yonsei University
Hyun-Joong Kim
Hyun-Joong Kim Seoul National University
Sung-Hoon Kim
Sung-Hoon Kim Yonsei University
Hyunjung Kim
Hyunjung Kim Hanyang University
Amir Mirmiran
Amir Mirmiran The University of Texas at Tyler
Hyoungkwan Kim
Hyoungkwan Kim Yonsei University
Shengwei Wang
Shengwei Wang Hong Kong Polytechnic University

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