Classification and Prediction Using Artificial Neural Networks

Folino, Molly; Staugler, Laura; Fitzpatrick, Anna

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Classification and Prediction Using Artificial Neural Networks

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Machine learning techniques have gained popularity in solving complex problems in areas such as biology, mathematics, computer science, and many other applications. This major qualifying project explores various machine learning methods such as linear discriminant analysis, quadratic discriminant analysis, support vector machines, and pattern recognition neural networks for data classification. We then focus on neural networks applied to solving ordinary differential equations to make predictions from a trained model. We compare these results to data assimilation using an Ensemble Kalman Filter, noting differences in the requirements of each method.

This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

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