Preparing input data for sensitivity analysis of an air pollution model by using high-performance supercomputers and algorithms

DOI10.1016/j.camwa.2015.07.020zbMath1443.91003OpenAlexW1817726229MaRDI QIDQ2006562

Vassil Alexandrov, Tzvetan Ostromsky, Ivan T. Dimov, Zahari Zlatev

Publication date: 11 October 2020

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.camwa.2015.07.020

zbMATH Keywords

performancesensitivity analysisparallel algorithmsupercomputerspeed-upair pollution model

Mathematics Subject Classification ID

Environmental economics (natural resource models, harvesting, pollution, etc.) (91B76) Parallel numerical computation (65Y05) Computational methods for problems pertaining to game theory, economics, and finance (91-08)

Cites Work

• Sensitivity studies of pollutant concentrations calculated by the UNI-DEM with respect to the input emissions
• Operator splitting and commutativity analysis in the Danish Eulerian model
• Making best use of model evaluations to compute sensitivity indices
• Studying the sensitivity of pollutants' concentrations caused by variations of chemical rates
• Computational and numerical challenges in environmental modelling
• Sensitivity Analysis of a Large-Scale Air Pollution Model: Numerical Aspects and a Highly Parallel Implementation
• Exact Error Estimates and Optimal Randomized Algorithms for Integration
• Sensitivity Analysis in Practice
• Monte Carlo estimators for small sensitivity indices
• Monte Carlo Methods for Applied Scientists
• Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates
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