An ArcGIS Tool for Modeling the Climate Envelope with Feed-Forward ANN

Bede-Fazekas, Ákos [Bede-Fazekas, Ákos (ökológiai modellezés), author] Department of Garden and Open Space Design (CUB); Horváth, Levente [Horváth, Levente (Matematika, biome...), author]; J. Trájer, Attila [Trájer, Attila János (vektor ökológia, ...), author] MTA-PE Limnoecology Research Group (UP / FE / IAESL / DL); Gregorics, Tibor [Gregorics, Tibor (Informatika), author] Programozáselmélet és Szoftvertechnológiai Tanszék (ELTE / ELU FoI / ICS)

English Scientific Article (Journal Article)
Published: APPLIED ARTIFICIAL INTELLIGENCE 0883-9514 29 (3) pp. 233-242 2015
  • SJR Scopus - Artificial Intelligence: Q3
    This paper is about the development and the application of an ESRI ArcGIS tool which implements multi-layer, feed-forward artificial neural network (ANN) to study the climate envelope of species. The supervised learning is achieved by backpropagation algorithm. Based on the distribution and the grids of the climate (and edaphic data) of the reference and future periods the tool predicts the future potential distribution of the studied species. The trained network can be saved and loaded. A modeling result based on the distribution of European larch (Larix decidua Mill.) is presented as a case study.
    Citation styles: IEEEACMAPAChicagoHarvardCSLCopyPrint
    2022-01-22 06:51