Increasing model efficiency by dynamically changing model representations

Authored by Randall Gray, Simon Wotherspoon

Date Published: 2012-04

DOI: 10.1016/j.envsoft.2011.08.012

Sponsors: No sponsors listed

Platforms: No platforms listed

Model Documentation: ODD Mathematical description

Model Code URLs: Model code not found

Abstract

There are a number of strategies to deal with modelling large complex systems such as large marine ecosystems. These systems are often comprised of many submodels, each contributing to the overall trajectory of the system. The balance between the acceptable modelling error and the run-time often dictates the form of these submodels. There may be scope to improve the position of this balance point in both regards by structuring models so that submodels may change their algorithmic representation and state space in response to their local state and the state of the model as a whole. This paper uses an example system consisting of a single population of animals which periodically encounters a diffuse contaminant in a localised region as an example of such a system, and discusses the key issues that arise from the approach. Crown Copyright (C) 2011 Published by Elsevier Ltd. All rights reserved.

Tags

Individual-based model Agent-based models Contaminant uptake Equation-based model Integrated model Model efficiency Model structure population Forest growth