activity
20212025
most citedDevelopment of a hybrid machine-learning and optimization tool for performance-based solar shading design

2 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

An AI-driven framework for rapid and localized optimizations of urban open spaces

Pegah Eshraghi, Arman Nikkhah Dehnavi, Maedeh Mirdamadi +2

As urbanization accelerates, open spaces are increasingly recognized for their role in enhancing sustainability and well-being, yet they remain underexplored compared to built spac…

cs.LG20241 cited

Adopting Explainable-AI to investigate the impact of urban morphology design on energy and environmental performance in dry-arid climates

Pegah Eshraghi, Riccardo Talami, Arman Nikkhah Dehnavi +2

In rapidly urbanizing regions, designing climate-responsive urban forms is crucial for sustainable development, especially in dry arid-climates where urban morphology has a signifi…

cs.LG20222 cited

Development of a hybrid machine-learning and optimization tool for performance-based solar shading design

Maryam Daneshi, Reza Taghavi Fard, Zahra Sadat Zomorodian +1

Solar shading design should be done for the desired Indoor Environmental Quality (IEQ) in the early design stages. This field can be very challenging and time-consuming also requir…

cs.SD2021

A Machine-learning Framework for Acoustic Design Assessment in Early Design Stages

Reyhane Abarghooie, Zahra Sadat Zomorodian, Mohammad Tahsildoost +1

In time-cost scale model studies, predicting acoustic performance by using simulation methods is a commonly used method that is preferred. In this field, building acoustic simulati…

cs.LG20211 cited

A machine-learning framework for daylight and visual comfort assessment in early design stages

Hanieh Nourkojouri, Zahra Sadat Zomorodian, Mohammad Tahsildoost +1

This research is mainly focused on the assessment of machine learning algorithms in the prediction of daylight and visual comfort metrics in the early design stages. A dataset was…