Search Results - "Moon, Jin Woo"

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  1. 1

    Improving sustainability of ever-changing building spaces affected by users’ fickle taste: A focus on human comfort and energy use by Moon, Jin Woo, Ahn, Jonghoon

    Published in Energy and buildings (01-02-2020)
    “…•A network-based model is proposed to improve indoor thermal comfort and energy efficiency in buildings.•Deterministic control strategies examine user's…”
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    Journal Article
  2. 2

    Performance of ANN-based predictive and adaptive thermal-control methods for disturbances in and around residential buildings by Moon, Jin Woo

    Published in Building and environment (01-02-2012)
    “…This study aimed at investigating an advanced residential thermal-control method through developing ANN (Artificial Neural Network)-based thermal-control…”
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    Journal Article
  3. 3

    Comparative performance analysis of the artificial-intelligence-based thermal control algorithms for the double-skin building by Moon, Jin Woo

    Published in Applied thermal engineering (05-12-2015)
    “…This study aimed at developing artificial-intelligence-(AI)-theory-based optimal control algorithms for improving the indoor temperature conditions and heating…”
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    Journal Article
  4. 4

    Thermostat strategies impact on energy consumption in residential buildings by Moon, Jin Woo, Han, Seung-Hoon

    Published in Energy and buildings (01-02-2011)
    “…This paper identifies the impact of thermostat strategies on heating and cooling energy consumptions in buildings, thus suggesting the importance of a database…”
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    Journal Article
  5. 5

    Climate-zone-dependent applicability of semi-transparent cadmium-telluride-type solar cells as a building material with display characteristics by Rang Park, Bo, Won Kim, Tae, Yeon Hyun, Ji, Woo Moon, Jin

    Published in Energy and buildings (15-05-2023)
    “…•The energy performance of solar signage windows in buildings was simulated.•The study covers various climates, window-to-wall ratios, and solar signage…”
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    Journal Article
  6. 6

    ANN-based thermal control models for residential buildings by Moon, Jin Woo, Kim, Jong-Jin

    Published in Building and environment (01-07-2010)
    “…This study aimed to develop an Artificial Neural Network (ANN)-based advanced thermal control method for creating more comfortable thermal environments in…”
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    Journal Article
  7. 7

    Development of an energy cost prediction model for a VRF heating system by Park, Bo Rang, Choi, Eun Ji, Hong, Jongin, Lee, Je Hyeon, Moon, Jin Woo

    Published in Applied thermal engineering (25-07-2018)
    “…•A predictive and adaptive ANN model was developed for controlling heating system.•The model predicted heating energy cost for the different variable…”
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    Journal Article
  8. 8

    A Comparative Study Between Thermostat/Hygrometer-Based Conventional and Artificial Neural Network-Based Predictive/Adaptive Thermal Controls in Residential Buildings by Moon, Jin Woo, Han, Seung-Hoon

    “…This study aimed at testing the feasibility of employing artificial neural network (ANN)-based predictive and adaptive control logics to improve thermal…”
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    Journal Article
  9. 9

    Performance Evaluation of Control Methods for PV-Integrated Shading Devices by Jung, Sung Kwon, Kim, Youngchul, Moon, Jin Woo

    Published in Energies (Basel) (01-06-2020)
    “…This study aimed to develop a building-integrated photovoltaic (BIPV) device and optimal control methods that increase the photovoltaic (PV) efficiency and…”
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  10. 10

    A new integrated framework to fault detection and diagnosis of air handling unit: Emphasizing the impact of symptoms by Hwan Cha, Jae, Kyu Park, Jun, Hyeon Chi, Chang, Hun Yeon, Sang, Ho Kim, Chul, Woo Moon, Jin, Ho Lee, Kwang

    Published in Energy and buildings (15-09-2024)
    “…•18 fault types of AHU are assessed by impacts to symptoms.•18 fault types are categorized into three levels based on symptom severity.•Various machine…”
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    Journal Article
  11. 11

    Development of an artificial neural network model based thermal control logic for double skin envelopes in winter by Moon, Jin Woo, Yoon, Sung-Hoon, Kim, Sooyoung

    Published in Building and environment (01-03-2013)
    “…This study proposes an Artificial Neural Network (ANN)-based thermal control method for double skin envelope buildings in winter. A thermal control logic for…”
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    Journal Article
  12. 12

    Development of Occupant Pose Classification Model Using Deep Neural Network for Personalized Thermal Conditioning by Choi, Eun Ji, Yoo, Yongseok, Park, Bo Rang, Choi, Young Jae, Moon, Jin Woo

    Published in Energies (Basel) (01-01-2020)
    “…This study aims to propose a pose classification model using indoor occupant images. For developing the intelligent and automated model, a deep learning neural…”
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    Journal Article
  13. 13

    Development of a Deep Neural Network Model for Estimating Joint Location of Occupant Indoor Activities for Providing Thermal Comfort by Choi, Eun Ji, Moon, Jin Woo, Han, Ji-hoon, Yoo, Yongseok

    Published in Energies (Basel) (01-02-2021)
    “…The type of occupant activities is a significantly important factor to determine indoor thermal comfort; thus, an accurate method to estimate occupant activity…”
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    Journal Article
  14. 14

    Performance evaluation of artificial neural network-based variable control logic for double skin enveloped buildings during the heating season by Kim, Sooyoung, Lee, Ji-Hyun, Moon, Jin Woo

    Published in Building and environment (01-12-2014)
    “…This study describes integrated logic for an artificial neural network (ANN) to control heating devices on a continuous basis. Two ANN-based control logic…”
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    Journal Article
  15. 15

    Improvement in Energy Performance of Building Envelope Incorporating Electrochromic Windows (ECWs) by Park, Bo Rang, Hong, Jongin, Choi, Eun Ji, Choi, Young Jae, Lee, Choonyeob, Moon, Jin Woo

    Published in Energies (Basel) (26-03-2019)
    “…The present study sets out to review the thermal and optical properties of electrochromic windows (ECWs) through an analysis of the improvement in the energy…”
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  16. 16

    Comparative study of artificial intelligence-based building thermal control methods – Application of fuzzy, adaptive neuro-fuzzy inference system, and artificial neural network by Moon, Jin Woo, Jung, Sung Kwon, Kim, Youngchul, Han, Seung-Hoon

    Published in Applied thermal engineering (01-10-2011)
    “…This study’s aim is to develop diverse Artificial Intelligence-based (AI-based) thermal control logics and to compare their performances for identifying…”
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    Journal Article
  17. 17

    ANN-Based Prediction and Optimization of Cooling System in Hotel Rooms by Moon, Jin Woo, Kim, Kyungjae, Min, Hyunsuk

    Published in Energies (Basel) (01-10-2015)
    “…This study aimed at developing an artificial-neural-network (ANN)-based model that can calculate the required time for restoring the current indoor temperature…”
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    Journal Article
  18. 18

    Application of control logic for optimum indoor thermal environment in buildings with double skin envelope systems by Moon, Jin Woo, Lee, Ji-Hyun, Kim, Sooyoung

    Published in Energy and buildings (01-12-2014)
    “…•Rule-based and artificial neural network(ANN)-based control logic were developed.•Detailed rules of logic were effective to keep temperature within comfort…”
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    Journal Article
  19. 19

    Accuracy Analysis of DNN-Based Pose-Categorization Model and Activity-Decision Algorithm by Park, Bo Rang, Choi, Eun Ji, Choi, Young Jae, Moon, Jin Woo

    Published in Energies (Basel) (01-02-2020)
    “…The objective of this study is to develop (1) a pose-categorization model that classifies the poses of an occupant based on their image in an indoor space and…”
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    Journal Article
  20. 20

    Thermal Comfort, Energy and Cost Impacts of PMV Control Considering Individual Metabolic Rate Variations in Residential Building by Hong, Sung, Lee, Jong, Moon, Jin, Lee, Kwang

    Published in Energies (Basel) (01-07-2018)
    “…To date, most of the indoor environment control is based on the dry-bulb air temperature, which is one of the simplified control methods having the limitation…”
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