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Physical Sciences and Mathematics Commons™
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- Anthropogenic Noise (1)
- Artificial Night Light (1)
- Convolutional Neural Network (1)
- Debris Flow (1)
- ECG (1)
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- Feature Extraction (1)
- Functional Traits (1)
- Machine Learning (1)
- Multi-Species Modeling (1)
- Plant-Pollinator Communities (1)
- Post-Fire (1)
- Predictive Model (1)
- Principal Components Analysis (1)
- Production Forecasting (1)
- Pruning (1)
- Recruitment (1)
- Shale Gas (1)
- Shear Resistance (1)
- Synergistic Interaction (1)
- Vs30 (1)
Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
Incorporating Shear Resistance Into Debris Flow Triggering Model Statistics, Noah J. Lyman
Incorporating Shear Resistance Into Debris Flow Triggering Model Statistics, Noah J. Lyman
Master's Theses
Several regions of the Western United States utilize statistical binary classification models to predict and manage debris flow initiation probability after wildfires. As the occurrence of wildfires and large intensity rainfall events increase, so has the frequency in which development occurs in the steep and mountainous terrain where these events arise. This resulting intersection brings with it an increasing need to derive improved results from existing models, or develop new models, to reduce the economic and human impacts that debris flows may bring. Any development or change to these models could also theoretically increase the ease of collection, processing, and …
Sensory Stressors Impact Species Responses Across Local And Continental Scales, Ashley A. Wilson
Sensory Stressors Impact Species Responses Across Local And Continental Scales, Ashley A. Wilson
Master's Theses
Pervasive growth in industrialization and advances in technology now exposes much of the world to anthropogenic night light and noise (ANLN), which pose a global environmental challenge in terrestrial environments. An estimated one-tenth of the planet’s land area experiences artificial light at night — and that rises to 23% if skyglow is included. Moreover, anthropogenic noise is associated with urban development and transportation networks, as the ecological impact of roads alone is estimated to affect one-fifth of the total land cover of the United States and is increasing in space and intensity. Existing research involving impacts of light or noise …
Combining Machine Learning And Empirical Engineering Methods Towards Improving Oil Production Forecasting, Andrew J. Allen
Combining Machine Learning And Empirical Engineering Methods Towards Improving Oil Production Forecasting, Andrew J. Allen
Master's Theses
Current methods of production forecasting such as decline curve analysis (DCA) or numerical simulation require years of historical production data, and their accuracy is limited by the choice of model parameters. Unconventional resources have proven challenging to apply traditional methods of production forecasting because they lack long production histories and have extremely variable model parameters. This research proposes a data-driven alternative to reservoir simulation and production forecasting techniques. We create a proxy-well model for predicting cumulative oil production by selecting statistically significant well completion parameters and reservoir information as independent predictor variables in regression-based models. Then, principal component analysis (PCA) …
Neural Network Pruning For Ecg Arrhythmia Classification, Isaac E. Labarge
Neural Network Pruning For Ecg Arrhythmia Classification, Isaac E. Labarge
Master's Theses
Convolutional Neural Networks (CNNs) are a widely accepted means of solving complex classification and detection problems in imaging and speech. However, problem complexity often leads to considerable increases in computation and parameter storage costs. Many successful attempts have been made in effectively reducing these overheads by pruning and compressing large CNNs with only a slight decline in model accuracy. In this study, two pruning methods are implemented and compared on the CIFAR-10 database and an ECG arrhythmia classification task. Each pruning method employs a pruning phase interleaved with a finetuning phase. It is shown that when performing the scale-factor pruning …