Alexander W Olson
Biographic Data
| ID | 6361697 |
|---|---|
| NAME | Alexander W Olson |
| GIVEN NAMES | Alexander W |
| FAMILY NAME | Olson |
| SIGNATURE | OLSON A W |
| AFFILIATIONS | University of Toronto |
| ORCID | 0000-0002-6593-2779 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 6 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Image‐based prediction of residential building attributes with deep learning
This study estimates building attributes—floor area and age—using image‐based machine learning. Building age and floor area are key inputs to the studies of urban metabolism, material stocks and flows, and embodied greenhouse gases (GHGs) in the built environment. However, these data are challenging to generate and maintain using traditional survey methods, their availability is uneven and often, even when available, very uncertain. Improving our…
Classification and Regression via Integer Optimization for Neighborhood Change
This article applies a method we term “predictive clustering” to cluster neighborhoods. Much of the literature in this direction is based on groupings built using intrinsic characteristics of each observation. Our approach departs from this framework by delineating clusters based on how the neighborhood’s features respond to a particular outcome of interest (e.g., income change). To do so, we leverage a classification and regression via integer o…
Reading the city through its neighbourhoods
Reading the city through its neighbourhoods
Classification and Regression via Integer Optimization for Neighborhood Change
This article applies a method we term “predictive clustering” to cluster neighborhoods. Much of the literature in this direction is based on groupings built using intrinsic characteristics of each observation. Our approach departs from this framework by delineating clusters based on how the neighborhood’s features respond to a particular outcome of interest (e.g., income change). To do so, we leverage a classification and regression via integer o…
Image‐based prediction of residential building attributes with deep learning
This study estimates building attributes—floor area and age—using image‐based machine learning. Building age and floor area are key inputs to the studies of urban metabolism, material stocks and flows, and embodied greenhouse gases (GHGs) in the built environment. However, these data are challenging to generate and maintain using traditional survey methods, their availability is uneven and often, even when available, very uncertain. Improving our…
Artificial Intelligence (3 works) · Computer Science (3 works) · Deep learning (2 works) · Mathematics (2 works) · Artificial Intelligence (1 work) · Autoencoder (1 work) · Bayesian Methods and Mixture Models (1 work) · Building Energy and Comfort Optimization (1 work) · Cluster (spacecraft) (1 work) · Cluster analysis (1 work)