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Material Evaluation And Structural Monitoring Of Early-Age Masonry Structures, Kyle Dunphy
Material Evaluation And Structural Monitoring Of Early-Age Masonry Structures, Kyle Dunphy
Electronic Thesis and Dissertation Repository
During the initial construction period, “early-age” masonry walls are susceptible to lateral loads induced by wind or earthquake, which may result in damages or catastrophic failures. To mitigate such consequences at construction sites, temporary bracings are adopted to provide lateral support to masonry walls until they are matured enough to serve as the inherent lateral system of the structure. However, current temporary bracing guidelines provide oversimplified design due to the lack of available information on the material properties of early-age masonry. Moreover, there are no existing techniques for monitoring masonry walls to detect cracks due to construction activities. …
Cluster-Based Chained Transfer Learning For Energy Forecasting With Big Data, Yifang Tian
Cluster-Based Chained Transfer Learning For Energy Forecasting With Big Data, Yifang Tian
Electronic Thesis and Dissertation Repository
Smart meter popularity has resulted in the ability to collect big energy data and has created opportunities for large-scale energy forecasting. Machine Learning (ML) techniques commonly used for forecasting, such as neural networks, involve computationally intensive training typically with data from a single building/group to predict future consumption for that same building/group. With hundreds of thousands of smart meters, it becomes impractical or even infeasible to individually train a model for each meter. Consequently, this paper proposes Cluster-Based Chained Transfer Learning (CBCTL), an approach for building neural network-based models for many meters by taking advantage of already trained models through …