Model uncertainty analysis using data analytics for life-cycle assessment (LCA) applications
Purpose Objective uncertainty quantification (UQ) of a product life-cycle assessment (LCA)
is a critical step for decision-making. Environmental impacts can be measured directly or by …
is a critical step for decision-making. Environmental impacts can be measured directly or by …
Selection of surrogate modeling techniques for surface approximation and surrogate-based optimization
Surrogate models are used to map input data to output data when the actual relationship
between the two is unknown or computationally expensive to evaluate for several …
between the two is unknown or computationally expensive to evaluate for several …
Efficient surrogate model development: impact of sample size and underlying model dimensions
This study compares eight surrogate-model construction approaches using computational
experiments. The construction approaches considered include: Artificial Neural Networks …
experiments. The construction approaches considered include: Artificial Neural Networks …
Surrogate model selection for design space approximation and surrogatebased optimization
Surrogate models are used to map input data to output data when the actual relationship
between the two is unknown or computationally expensive to evaluate for sensitivity …
between the two is unknown or computationally expensive to evaluate for sensitivity …
Surrogate modeling of fugacity coefficients using adaptive sampling
Complex thermodynamic models such as the perturbed chain statistical associating fluid
theory (PC-SAFT) model describe the phase equilibria in a chemical process in a very …
theory (PC-SAFT) model describe the phase equilibria in a chemical process in a very …
Leveraging supplementary modalities in automated real estate valuation using comparative judgments and deep learning
Purpose In this study the authors aim to outline new ways of information extraction for
automated valuation models, which in turn would help to increase transparency in valuation …
automated valuation models, which in turn would help to increase transparency in valuation …
Revised learning based evolutionary assistive paradigm for surrogate selection (LEAPS2v2)
Selecting appropriate surrogate models is crucial. This article upgrades our learning-based
surrogate selection paradigm (LEAPS2) to LEAPS2v2. Its key features include: modeling …
surrogate selection paradigm (LEAPS2) to LEAPS2v2. Its key features include: modeling …
System resilience through health monitoring and reconfiguration
We demonstrate an end-to-end framework to improve the resilience of man-made systems to
unforeseen events. The framework is based on a physics-based digital twin model and three …
unforeseen events. The framework is based on a physics-based digital twin model and three …
Zone-wise surrogate modelling (ZSM) of univariate systems
Many complex systems display distinctly different behaviors across regions, zones, or sub-
domains. A single surrogate may not suffice in modelling such systems. A better approach …
domains. A single surrogate may not suffice in modelling such systems. A better approach …
A new termination criterion for sampling for surrogate model generation using partial least squares regression
This paper proposes a new incremental sampling method for the generation of surrogate
models based on the application of partial least squares regression (PLSR) as a termination …
models based on the application of partial least squares regression (PLSR) as a termination …