Using tensor calculus for scenario modelling

Authors:
Manfred Lenzen;Bonnie Mcbain
Affiliations:
ISA, School of Physics A28, The University of Sydney, NSW 2006, Australia;School of Environmental and Life Sciences, Discipline of Geography, Bldg SRR, University of Newcastle, Callaghan NSW 2308, Australia
Venue:
Environmental Modelling & Software
Year:
2012

Citing 5
Cited 0

Algorithm 862: MATLAB tensor classes for fast algorithm prototyping

ACM Transactions on Mathematical Software (TOMS)
Efficient MATLAB Computations with Sparse and Factored Tensors

SIAM Journal on Scientific Computing
An integrated approach to modelling land-use change on continental and global scales

Environmental Modelling & Software
Evaluation of an integrated land use change model including a scenario analysis of land use change for continental Africa

Environmental Modelling & Software
Stochasticity in the image greenhouse model

Mathematical and Computer Modelling: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

We have demonstrated the benefits of sparse tensor calculus for finite-difference techniques that are widely applied to Integrated Assessment (IA). Using a tensor toolbox for Matlab, we have developed efficient code for progressing a system of state variables connected by a large variety of interaction types. Using a small example of twenty variables across three countries, we demonstrate how the tensor formalism allows not only for compact and fast scenario modelling, but also for straightforward implementation of sensitivity and Monte-Carlo analyses, as well as Structural Decomposition Analysis. In particular, we show how sparse tensor code can be exploited in order to search for potentially important, but yet unknown relationships in the interaction network between all variables.