A note on model selection based on the percentage of accuracy-precision

[+] Author and Article Information
Ehsan Heidaryan

Department of Chemical Engineering, Engineering School, University of São Paulo (USP), Caixa Postal 61548, 05424-970, São Paulo, SP, Brazil; Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom

1Corresponding author.

ASME doi:10.1115/1.4041844 History: Received October 16, 2018; Revised October 22, 2018


Mathematical methods such as empirical correlations, analytical models, numerical simulations, and data-intensive computing (data-driven models) are key in the modeling of energy science and engineering. Accrediting of different models and deciding on the best method however, is a serious challenge even for experts, as the application of models are not limited only to estimations, but to predictions and derivative properties. In this note, by combining meaningful metrics of accuracy and precision, a new metric for determining the best-in-class method was defined.

Copyright (c) 2018 by ASME
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