[Case Study] Parameter Timing Prediction 'DTEmpower'

Solve data characteristics and model training issues! Ultimately, the R2 index of the predictive model improved from 0.68 to 0.94.

We would like to introduce an application case of timing prediction for parameters of our intelligent data modeling software "DTEmpower." This product is equipped with graphical process construction features, allowing all data and model operations to be performed simply by manipulating the modules within the toolbox. In the time series forecasting problem, our software addressed issues related to data characteristics and model training, ultimately improving the R2 index of the prediction model from 0.68 to 0.94. [Case Overview] - Faced with a complex dynamic biochemical process model characterized by strong external interference, time-varying factors, coupling, and non-linearity, we built a data-driven system based on a large amount of measurement data. - By rationally selecting external features and introducing feature engineering techniques such as MDI/PCA, we not only enhanced the richness of input information but also improved model prediction accuracy and mitigated issues arising from excessive input. *For more details, please download the PDF or feel free to contact us.

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