Process inputs
One scenario, shared by both predictors
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ENGINEERING × MACHINE LEARNING
One operating point. Two emissions. Explore what the models predict—and how they performed.
One scenario, shared by both predictors
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THE EVIDENCE BEHIND THE ESTIMATE
Saved predictions, measured outcomes and a closer look at error.
Charts follow each predictor’s model selection.
Development plots use earlier fold fits, not the main fitted artifact. Pooled metrics use individual saved observations; R² can be negative. Later years were previously inspected and are retrospective evidence.
UNDERSTAND THE INVESTIGATION
A historical virtual sensor: estimate concurrent emissions from nine turbine measurements.
Main models fit all 2011–2013 observations. Development folds fit 2011 to assess 2012, then fit 2011–2012 to assess 2013. Configurations are selected on those folds.
2014–2015 stay outside model fitting. Since those years have been inspected, subsequent comparisons are retrospective. Strong training fit does not establish useful later performance.
Separate models fit 2011 and calibrate on 2012. Their nominal 90% or 95% intervals can under-cover later observations, especially NOx. They are not intervals for the main 2011–2013 models.
No fabricated dates, unit conversions, sensor corrections or outlier removal. Source row order does not prove uninterrupted hourly coverage. This is concurrent regression, not a forecast of future emissions.
All source observations are retained. Associations are descriptive and do not establish causation.
Public UCI Gas Turbine CO and NOx Emission Data Set · DOI 10.24432/C5WC95 · CC BY 4.0. An engineering learning project and interactive proof of concept.
CHECK THE CALCULATIONS
Independent checks of calculations, data handling, model pipelines and reporting.
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Verification checks software and reporting. Predictive validation examines behaviour on observations outside fitting. Neither certifies sensor accuracy or operational suitability.
FOLLOW THE SOURCE
Methods, experiment comparisons, original charts and downloadable records.