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Coupling convolutional neural networks with gated recurrent units to model illuminance distribution from light pipe systems

  • Published:2023-06 Issue: Volume:237 Page:110276
  • ISSN:0360-1323
  • Container-title:Building and Environment
  • language:en
  • Short-container-title:Building and Environment

Author:

Ngarambe JackORCID,Duhirwe Patrick NzivugiraORCID,Van Quang Tran,Nzarigema Jean d’Amour,Yun Geun YoungORCID

Funder

Korea Institute of Energy Technology Evaluation and Planning

Ministry of Education

Ministry of Trade, Industry and Energy

National Research Foundation of Korea

Publisher

Elsevier BV

Subject

Building and Construction,Geography, Planning and Development,Civil and Structural Engineering,Environmental Engineering

Reference33 articles.

1. Estimation of energy savings due to the integration of daylight with artificial lighting in classrooms;Al-Ashwal;Adv. Sci. Lett.,2017

2. Global urbanization projections for the shared socioeconomic pathways;Jiang;Global Environ. Change,2017

3. LRT Digest 2 Tubular daylight guidance systems;Carter;Light. Res. Technol.,2014

4. Enhancing the performance of a passive tubular daylighting device using a parabolic-profile collector;Bisht;Light. Res. Technol.,2020

5. Daylight in buildings based on tubular light guides;Darula;J. Build. Eng.,2021

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