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Application of Deep Learning in Generating Desired Design Options: Experiments Using Synthetic Training Dataset
In this study, an object recognition problem is investigated to initially predict the label of unseen sample images based on training dataset consisting of different types of synthetic 2D shapes; later, a generative DL algorithm is applied to be trained and generate new shapes for given labels.
Application of Classification and Feature Selection in Building Energy Simulations
The best design alternative is selected based on the LDA results and the key input parameters are determined based on the PCA and EFS methods.
A machine-learning framework for daylight and visual comfort assessment in early design stages
A dataset was primarily developed from 2880 simulations derived from Honeybee for Grasshopper.
A Machine-learning Framework for Acoustic Design Assessment in Early Design Stages
In time-cost scale model studies, predicting acoustic performance by using simulation methods is a commonly used method that is preferred.
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