Implementing stochastic distribution within the utopia plane of primary producers using a hybrid genetic algorithm

Furze, James Nicholas; Qiao, Feng; Furze, James; Qaio, Feng; Zhu, Quanmin; Hill, Jennifer

Abstract

The two key variables in estimating the water-energy dynamic, which determines proportions of plant strategy components on a macro basis, are temperature and precipitation. Additionally, use of high-resolution elevation data facilitates formation of the fuzzy rule base for ordination of the strategical nodes. Application of adaptive neural fuzzy inference systems produces sets of rules, which may be minimised to increase the efficiency of modelling the distribution of plants and their characters. A modified objective genetic evolutionary algorithm was employed in this study to show the distribution of elements of strategies within a strength Pareto. Distribution of the elements showed an approximate Poisson curve in objective space that may be extrapolated to a real-numbered population via application of optimisation algorithms to reflect the stochastic organisation of the populations. © 2013 Inderscience Enterprises Ltd.

• Journal Article Type: Article
• Acceptance Date: Jan 1, 2013
• Publication Date: Jun 12, 2013
• Journal: International Journal of Computer Applications in Technology
• Print ISSN: 0952-8091
• Electronic ISSN: 1741-5047
• Publisher: Inderscience
• Peer Reviewed: Peer Reviewed
• Volume: 47
• Issue: 1
• Pages: 68-77
• DOI: https://doi.org/10.1504/IJCAT.2013.054303
• Keywords: water-energy dynamic; adaptive neural fuzzy inference systems; genetic algorithm; optimisation; stochastic organisation
• Public URL: https://uwe-repository.worktribe.com/output/938070
• Publisher URL: http://dx.doi.org/10.1504/IJCAT.2013.054303