Sensitivity analysis helps predict outcomes by varying key variables in financial models. It simplifies complex models, aids in understanding variable effects, and reduces uncertainty. This analysis ...

Abstract: Linear programming representations for discrete-event simulation provide an alternative approach for analyzing discrete-event simulations. This paper presents several formulations for G/G/m ...

This work presents the mathematical/theoretical framework of the “nth-Order Feature Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint ...

The majority of research predicted heating demand using linear regression models, but they did not give current building features enough context. Model problems such as Multicollinearity need to be ...

Department of Chemical Engineering, The Pennsylvania State University, State College, University Park, Pennsylvania 16802, United States ...

remove-circle Internet Archive's in-browser bookreader "theater" requires JavaScript to be enabled. It appears your browser does not have it turned on. Please see ...

Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China ...

Abstract: Linear programming (LP) is widely used for the economic dispatch of energy systems. Due to the increasing inhomogeneity of supply and storage technologies, the consideration of sector ...