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contributor authorAlves, Josivan Leite
contributor authorAlmeida Filho, Adiel Teixeira de
contributor authorBradaschia, Fabrício
contributor authorPalha, Rachel Perez
date accessioned2026-08-20T10:44:23Z
date available2026-08-20T10:44:23Z
date copyright2026/04/14
date issued2026
identifier otherJCEMD4.COENG-17897.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4311197
description abstractAbstractUrban expansion, driven by economic and technological development, has intensified building construction and increased energy demand. Over the last decade, this trend has become a global challenge due to the depletion of fossil fuel reserves and ...Practical ApplicationsThis study investigated how artificial intelligence models can enhance solar energy forecasting in diverse regions. By using data collected over time, the research compared the performance of three different predictive models to ...
publisherAmerican Society of Civil Engineers
titleSolarisBIM.AI: Smart Sustainable Building Planning with BIM-Based Solar-Production Estimation Using Machine-Learning Radiation Forecasts
typeJournal Article
journal volume152
journal issue6
journal titleJournal of Construction Engineering and Management
identifier doi10.1061/JCEMD4.COENG-17897
journal fristpage04026076-1
journal lastpage04026076-17
page17
treeJournal of Construction Engineering and Management:;2026:;Volume ( 152 ):;issue: 006
contenttypeFulltext


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