O'Hanley, J.R. (2009) NeuralEnsembles: A neural network based ensemble forecasting program for habitat and bioclimatic suitability analysis. Ecography, 32 (1). pp. 89-93. ISSN 0906-7590. (doi:10.1111/j.1600-0587.2008.05601.x) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:25472)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: http://dx.doi.org/10.1111/j.1600-0587.2008.05601.x |
Abstract
NeuralEnsembles is an integrated modeling and assessment tool for predicting areas of species habitat/bioclimatic suitability based on presence/absence data. This free, Windows based program, which comes with a friendly graphical user interface, generates predictions using ensembles of artificial neural networks. Models can quickly and easily be produced for multiple species and subsequently be extrapolated either to new regions or under different future climate scenarios. An array of options is provided for optimizing the construction and training of ensemble models. Main outputs of the program include text files of suitability predictions, maps and various statistical measures of model performance and accuracy.
Item Type: | Article |
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DOI/Identification number: | 10.1111/j.1600-0587.2008.05601.x |
Subjects: | H Social Sciences > H Social Sciences (General) |
Divisions: | Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
Depositing User: | Jesse O'Hanley |
Date Deposited: | 03 Sep 2010 15:45 UTC |
Last Modified: | 05 Nov 2024 10:05 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/25472 (The current URI for this page, for reference purposes) |
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