Abstract
This invention is potentially relevant in numerous areas/services. Many services rely upon measurements, which influence real-time decision making. Often the simplest approach to smoothen noisy data is to apply linear regression (e.g. line of best fit). However, such an assumption is not always the best and may result in less than optimal interpretation of the data. The algorithm outlined here is capable of selecting an appropriate model (based on data and SME input for the particular application) to improve the fit and interpretation/description of the data.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Baker Hughes Company, "Model-based Data Fitting", Technical Disclosure Commons, (March 10, 2025)
https://www.tdcommons.org/dpubs_series/7882