/Advanced-Prediction-of-Multi-stage-continuous-flow-manufacturing-process

Created data regression models to predict 15 unknown variables within 4% error at any plant condition. Denoised 11000 x 115 dataset, leading to 70% improvement in prediction accuracy. Used data engineering to produce features that were relevant to the target variables. Produced confusion matrices to determine relevant features for machine learning. Final prediction horizon of four times dataset timescale to within 5% error

Primary LanguageJupyter Notebook

Advanced Prediction of Multistage continuous flow manufacturing process

Created data regression models to predict 15 unknown variables within 4% error at any plant condition. Denoised 11000 x 115 dataset, leading to 70% improvement in prediction accuracy. Used data engineering to produce features that were relevant to the target variables. Produced confusion matrices to determine relevant features for machine learning. Final prediction horizon of four times dataset timescale to within 5% error