Cdm Smith Inc.

Patrick R McCafferty

Janardhanan Vinoth Upendra

T Sai Revanth

Zubair F Ghafoor

David L Ubert

Embodiments provide functionality to control real-world mechanical systems through the creation and deployment of machine learning models. An embodiment creates the machine learning model by extracting (i) an indication of efficiency and (ii) values of operational characteristics of one or more devices from one or more characteristic curves. Each characteristic curve corresponds to a respective device of one or more devices, in a mechanical system, functioning at a given speed. A training data set is created by determining efficiency and values of the operational characteristics for the mechanical system functioning with multiple combinations of the one or more devices operating at each of a plurality of speeds using the extracted indication of efficiency and extracted values of the operational characteristics. In turn, the machine learning model is trained with the created training dataset. Training configures the machine learning model to predict efficiency of the mechanical system based on operating data.

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Hanover, MA, United States of America

Patrick R McCafferty