Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 4 of 4 for “"Random Forest Classifier (RFC)"”.
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Low-Power Wireless Sensor Node with Edge Computing for Pig Behavior Classifications
… through WSN edge computing solution, in which a Random Forest Classifier (RFC) is trained and implemented into WSNs. The implementation of RFC on WSNs does not save power, but the RFC predicts animal behavior such that WSNs can adaptively adjust the data sampling frequency to reduce power …
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CLASSIFYING TCP NETWORK TRAFFIC FLOWS VIA TRAFFIC INTERACTION GRAPHS AND MACHINE LEARNING
… TCP streams using the 5-tuple definition from RFC6146. We then apply the traffic interaction graph (TIG) framework to these flows to capture burst patterns among signed packet lengths. Finally, we train these flows on a random forest classifier (RFC), a simple convolutional neural network …
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A Machine-Learning Based Approach to Predicting Waterborne Disease Outbreaks Caused by Hurricanes
… coastal counties using multiple linear (MLR) and random forest regression (RFR) models. Then, we developed a binary random forest classifier (RFC) model to predict waterborne disease outbreaks (e.g., 0: no outbreak and 1: outbreak). Results of this study showed that the highest coefficient of …
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Observing the Seasonal Evolution of Supraglacial Ponds in High Mountain Asia: A Supervised Classification Approach
… in the HMA region. An unsupervised k-means classifier is used to train a supervised Random Forest Classifier (RFC) in the Google Earth Engine platform. This study adapts algorithms used by Dell et al., (2021) for application in the HMA region. The classifier is trained on four spatially …