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Economics of wildfire suppression: Estimation of drivers of suppression expenditure and Risk preference experiments with wildfire management
DownloadSpring 2022
Public wildfire management agencies are presented with a momentous responsibility: to protect life, property and infrastructure from the devastation of wildland fire, while operating at a level of expenditure justifiable to taxpayers. At a time when climate change drives more extreme fire...
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Enhancing the Performance of Smart Grids via Applying Machine Learning Methods to Smart Meter Data
DownloadFall 2019
Conventional distribution systems need to undergo several updates to be able to meet modern energy requirements. While conventional grids have been able to satisfy the objectives they were designed for, lack of sensors and powerful communication systems, primitive control and management methods,...
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Fall 2023
Modelling agent preferences has applications in a range of fields including economics and increasingly, artificial intelligence. These preferences are not always known and thus may need to be estimated from observed behavior, in which case a model is required to map agent preferences to...
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Spring 2021
Temporal difference (TD) methods provide a powerful means of learning to make predictions in an online, model-free, and highly scalable manner. In the reinforcement learning (RL) framework, we formalize these prediction targets in terms of a (possibly discounted) sum of rewards, called the...
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Estimating Winter Road Friction Coefficients: An Integrated Approach using Machine Learning, Explainable AI, and Model Transferability
DownloadFall 2023
Ensuring road safety and efficient traffic movement through Winter Road Maintenance (WRM) operations is a pressing concern, particularly during harsh weather conditions. The challenge of accurately monitoring road friction coefficients, which play a crucial role in WRM, often leads to impractical...
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Fall 2024
Value-based reinforcement learning is an approach to sequential decision making in which decisions are informed by learned, long-horizon predictions of future reward. This dissertation aims to understand issues that value-based methods face and develop algorithmic ideas to address these issues....
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Finding Interesting Moments in Videos: Audio-visual and Unsupervised Video Highlight Detection
DownloadSpring 2022
Video is the dominant medium through which we consume information. Due to the sheer volume of video content, it is of great interest in the research community to develop automated ways to make this content manageable. In video highlight detection, our goal is to automatically find interesting...
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Harnessing Visual Analytics for Enhanced Winter Road Safety: A Framework for Continuous Road Surface Friction Estimation
DownloadFall 2023
Winter Road Surface Condition (RSC) monitoring currently relies on qualitative descriptors such as "bare lane," "partially snow-covered," and "fully snow-covered. These descriptors present two inherent problems—their subjective nature, which gives rise to measurement inconsistencies, and the...
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IDENTIFYING ADOLESCENTS AT RISK OF DEVELOPING NEGATIVE OUTCOMES AFTER RECEIVING OPIOID ANALGESICS FOR CHRONIC NON-CANCER PAIN MANAGEMENT USING MACHINE LEARNING ALGORITHMS
DownloadSpring 2023
Canada's prescription opioid dispensing rates have increased since the early 21st century and this has contributed to an increase in opioid-related morbidity and mortality. Adolescents are one of the most vulnerable age groups when it comes to experiencing morbidity and mortality related to...