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Skip to Search Results- 1Aftergood, Olivia SR
- 1Al Dallal, Ahmed
- 1Behsaz, Babak
- 1Berube, Paul N. J.
- 1Blouin, Karen D
- 1Brown, Daniel M.
- 13Department of Computing Science
- 9Department of Electrical and Computer Engineering
- 3Department of Civil and Environmental Engineering
- 2Department of Renewable Resources
- 1Department of Agricultural, Food, and Nutritional Science
- 1Department of Earth and Atmospheric Sciences
- 4Sander, Joerg (Computing Science)
- 2Reformat, Marek (Electrical and Computer Engineering)
- 1Ardakanian, Omid (Computing Science)
- 1Cockburn, Bruce (Department of Electrical and Computer Engineering)
- 1Deutsch, Clayton (Civil and Environmental Engineering)
- 1Dick, Scott (Department of Electrical and Computer Engineering)
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Fall 2012
Recent proliferation of low-cost and lightweight GPS tracking devices led to a large increase in the amounts of collected mobility data. The rapidly emerging field of location-based services requires accurate and informative knowledge mining from these large quantities of data. One such mobility...
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Fall 2017
Density-based clustering methods extract high density clusters which are separated by regions of lower density. HDBSCAN* is an existing algorithm for producing a density-based cluster hierarchy. To obtain clusters from this hierarchy it includes an instance of FOSC(Framework for Optimal Selection...
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Fall 2015
The objective of this thesis is to develop, implement and verify a theoretical framework based upon aggregation and mathematical programming for solving the long-term open pit production planning problem. The goal is to closely estimate the maximum net present value of the operation by providing...
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Fall 2011
An industrial construction enterprise operating in the City of Edmonton wants to improve its bidding strategies that are currently plagued with uncertainty, lack of information and historical price variability. The present research studies a compilation of documents obtained from company archives...
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Fall 2022
With the rapid development of smart grids, the detection of anomalies is essential to improve the quality and security protection of the grid. The identification of anomalies not only saves valuable time but also reduces maintenance costs. Due to the increasing deployment of distributed energy...
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Spring 2021
Deep learning has revolutionized many fields that process large amounts of data such as images, video, audio, speech, and text. Anomaly detection, however, is among the areas that still require major advancements. Based on the key traits of deep learning, which are the need for very little hand...
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Application of Machine Learning in the Big Data for Broiler Breeders Recorded by a Precision Feeding System
DownloadSpring 2021
A precision feeding (PF) system developed at the University of Alberta is an innovation in precise nutrition and management for broiler breeders. The PF system can automatically feed individual broiler breeders and record vast amounts of real-time data regarding the feeding activity of individual...
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Fall 2012
In this thesis, we present some approximation algorithms for the following clustering problems: Minimum Sum of Radii (MSR), Minimum Sum of Diameters (MSD), and Unsplittable Capacitated Facility Location. Given a metric (V, d) and an integer k, we consider the problem of partitioning the points...
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Fall 2015
In this thesis, we consider two closely related clustering problems, Min Sum k-Clustering (MSkC) and Balanced k-Median (BkM). In Min Sum k-clustering, one is given a graph and a parameter k, and has to partition the vertices in the graph into k clusters to minimize the sum of pairwise distances...
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Spring 2023
In this thesis, we present Approximation Schemes for the Min Sum k Clustering problem on a number of classes of graph metrics. In Min Sum k Clustering problem introduced by Sahni and Gonzalez [22] in 1976, given a graph G(V, E) with metric edge costs and parameter k, we are asked to partition V...