Mathematical methods such as empirical correlations, analytical models, numerical simulations, and data-intensive computing (data-driven models) are the key to 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 is 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.
Issue Section:
Discussion
References
1.
Houssainy
, S.
, Janbozorgi
, M.
, and Kavehpour
, P.
, 2018
, “Theoretical Performance Limits of an Isobaric Hybrid Compressed Air Energy Storage System
,” ASME J. Energy Resour. Technol.
, 140
(10
), p. 101201
.2.
ASCE Task Committee on Definition of Criteria for Evaluation of Watershed Models of the Watershed Management Committee, Irrigation and Drainage Division
, 1993
, “Criteria for Evaluation of Watershed Models
,” J. Irrig. Drain. Eng.
, 119
(3
), p. 429
.3.
Yang
, Z.
, Zhang
, Y.
, and Gao
, W.
, 2018
, “Improved Model of an Intermediate Point Enthalpy Control System for Enhancing Boiler Efficiency
,” ASME J. Energy Resour. Technol.
, 141
(2
), p. 022001
.4.
Sheridan
, R. P.
, 2013
, “Time-Split Cross-Validation as a Method for Estimating the Goodness of Prospective Prediction
,” J. Chem. Inf. Model.
, 53
(4
), p. 783
.5.
Nazeri
, M.
, Mercedes Maroto-Valer
, M.
, and Jukes
, E.
, 2018
, “Density of Carbon Dioxide With Impurities by Coriolis Flow Meter, Oscillation-Type Densitometer and Equations of State
,” Appl. Energy
, 212
, p. 162
.6.
Heidaryan
, E.
, and Jarrahian
, A.
, 2013
, “Natural Gas Viscosity Estimation Using Density Based Models
,” Can. J. Chem. Eng.
, 91
(6
), p. 1183
.7.
Caswell
, H.
, 1976
, “The Validation Problem
,” Syst. Anal. Simul. Ecol.
, 4
, p. 313
.8.
Márquez-Nolasco
, A.
, Conde-Gutiérrez
, R. A.
, Hernández
, J. A.
, Huicochea
, A.
, Siqueiros
, J.
, and Pérez
, O. R.
, 2018
, “Optimization and Estimation of the Thermal Energy of an Absorber With Graphite Disks by Using Direct and Inverse Neural Network
,” ASME J. Energy Resour. Technol.
, 140
(2
), p. 020906
.9.
Wei
, N.
, Li
, C.
, Li
, C.
, Xie
, H.
, Du
, Z.
, Zhang
, Q.
, and Zeng
, F.
, 2019
, “Short-Term Forecasting of Natural Gas Consumption Using Factor Selection Algorithm and Optimized Support Vector Regression
,” ASME J. Energy Resour. Technol.
, 141
(3
), p. 032701
.10.
Tofallis
, C.
, 2015
, “A Better Measure of Relative Prediction Accuracy for Model Selection and Model Estimation
,” J. Oper. Res. Soc.
, 66
(8
), p. 1352
.11.
Moussa
, T.
, Elkatatny
, S.
, Mahmoud
, M.
, and Abdulraheem
, A.
, 2018
, “Development of New Permeability Formulation From Well Log Data Using Artificial Intelligence Approaches
,” ASME J. Energy Resour. Technol.
, 140
(7
), p. 072903
.12.
Kvålseth
, T. O.
, 1985
, “Cautionary Note About R2
,” Am. Stat.
, 39
(4
), p. 279
.13.
Paul
, A.
, Bhowmik
, S.
, Panua
, R.
, and Debroy
, D.
, 2018
, “Artificial Neural Network-Based Prediction of Performances-Exhaust Emissions of Diesohol Piloted Dual Fuel Diesel Engine Under Varying Compressed Natural Gas Flowrates
,” ASME J. Energy Resour. Technol.
, 140
(11
), p. 112201
.14.
Asuero
, A. G.
, Sayago
, A.
, and Gonzalez
, A. G.
, 2006
, “The Correlation Coefficient: An Overview
,” Crit. Rev. Anal. Chem.
, 36
(1
), p. 41
.15.
Legates
, D. R.
, and McCabe
, G. J.
, Jr., 1999
, “Evaluating the Use of “Goodness‐of‐Fit” Measures in Hydrologic and Hydroclimatic Model Validation
,” Water Resour. Res.
, 35
(1
), p. 233
.16.
Taylor
, J.
, 1997
, Introduction to Error Analysis, the Study of Uncertainties in Physical Measurements
, 2nd ed., University Science Books
, Sausalito, CA.17.
Chapra
, S. C.
, and Raymond
, P. C.
, 2016
, Numerical Methods for Engineers
, 6th ed., McGraw-Hill
, New York.18.
Shepperd
, M.
, and Schofield
, C.
, 1997
, “Estimating Software Project Effort Using Analogies
,” IEEE Trans. Softw. Eng.
, 23
(11
), p. 736
.19.
Nash
, J. E.
, and Sutcliffe
, J. V.
, 1970
, “River Flow Forecasting Through Conceptual Models—Part I: A Discussion of Principles
,” J. Hydrol.
, 10
(3
), p. 282
.20.
Prasolov
, V. V.
, 2009
, Polynomials
, Vol. 11
, Springer Science & Business Media
, Berlin.21.
Wagner
, W.
, and Pruß
, A.
, 2002
, “The IAPWS Formulation 1995 for the Thermodynamic Properties of Ordinary Water Substance for General and Scientific Use
,” J. Phys. Chem. Ref. Data
, 31
(2
), p. 387
.22.
Leland
, T. W.
, and Chappelear
, P. S.
, 1968
, “The Corresponding States Principle—A Review of Current Theory and Practice
,” Ind. Eng. Chem.
, 60
(7
), p. 15
.23.
Arrhenius
, S.
, 1889
, “Über Die Reaktionsgeschwindigkeit Bei Der Inversion Von Rohrzucker Durch Säuren
,” Z. Phys. Chem.
, 4
(1
), p. 226
.24.
Guest
, P. G.
, 2012
, Numerical Methods of Curve Fitting
, Cambridge University Press
, Cambridge, UK.25.
Papadimitriou
, C. H.
, and Steiglitz
, K.
, 1998
, Combinatorial Optimization: Algorithms and Complexity
, Courier Corporation
, Mineola, NY.26.
Jarrahian
, A.
, Aghel
, B.
, and Heidaryan
, E.
, 2015
, “On the Viscosity of Natural Gas
,” Fuel
, 150
, p. 609
.27.
Kang
, P. S.
, Hwang
, J. Y.
, and Lim
, J. S.
, 2019
, “Flow Rate Effect on Wax Deposition Behavior in Single-Phase Laminar Flow
,” ASME J. Energy Resour. Technol.
, 141
(3
), p. 032903
.28.
Cheng
, C. L.
, and Garg
, G.
, 2014
, “Coefficient of Determination for Multiple Measurement Error Models
,” J. Multivar. Anal.
, 126
, p. 137
.29.
Yaws
, C. L.
, 2014
, Thermophysical Properties of Chemicals and Hydrocarbons
, 2nd ed., Elsevier
, Oxford, UK.Copyright © 2019 by ASME
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