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