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This document discusses the use of artificial neural network (ANN) proxy models for life cycle assessments (LCA) in the energy industry, highlighting their advantages over traditional quadratic regression models. It examines adaptive sampling methods to improve model accuracy while reducing computational time, using case studies on transportation fuels and natural gas pipelines. The findings indicate that ANN models significantly reduce errors and are more suitable for complex, nonlinear systems.

Author

erick

Language

EN