Connectionists: CfP 10th International Conference on Ecological Informatics (Jena, Germany September 24-28 2018)

[Antonino Staiano]

Call for papers Regular Session: Understanding species distribution,
population dynamics and phenology by machine learning. (Session Chairs:
Antonino Staiano, Alberto Lanzoni and Friedrich Recknagel)

within the general theme:
ECOLOGICAL DATA SYNTHESIS BY MACHINE LEARNING AND HYBRID MODELLING

Regular session 2.1: Understanding species distribution, population
dynamics and phenology by machine learning

Inferential modelling by machine learning techniques allows efficient and
user-friendly analysis and synthesis of highly complex ecological data.
Methods like random forest, quantile regression forest, Maxent, GARP have
been successfully applied for species distribution modelling of extensive
spatial data resulting in species response curves that describe a species’
response to a given habitat condition, and illustrate specific habitat
requirements for the species. Non-supervised artificial neural networks,
regression trees and canonical correspondence analyses allow to ordinate
and classify complex ecological data. Applications of support vector
machines, supervised artificial neural networks and evolutionary algorithms
to large spatial and temporal data allow to predict population dynamics and
reveal phenology.

This session welcomes papers on all aspects of inferential modelling of
ecological data by means of novel machine learning techniques.

The call is available at http://icei2018.uni-jena.de/calls/.

For full consideration please submit your abstract to the session via
EasyChair by March 18, 2018.

Antonino Staiano
Department of Science and Technology
University of Naples Parthenope, Naples, Italy
antonino.staiano at uniparthenope.it
************************************************************
************************************************

Antonino Staiano, PhD
Assistant Professor
Dept. Science and Technology
University of Naples Parthenope, Italy
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20180205/3acb821c/attachment.html>