Artificial neuronal networks : application to ecology and evolution /

Bibliographic Details
Other Authors: Lek, Sovan, 1952-, Guégan, Jean-François
Format: Book
Language:English
Published: New York : Springer, 2000.
Series:Environmental science (Berlin, Germany)
Subjects:
Table of Contents:
  • Neuronal Networks: Algorithms and Architectures for Ecologist and Evolutionary Ecologists
  • Predicting Ecologically Important Vegetation Variables from Remotely Sensed Optical/Radar Data Using Neuronal Networks
  • Soft Mapping of Coastal Vegetation from Remotely Sensed Imagery with a Feed-Forward Neuronal Network
  • Ultrafast Estimationof Neotropical Forest DBH Distributions from Ground Based Photographs Using a Neuronal Network
  • Normalized Difference Vegetation Index Estimation in Grasslands of Patagonia by Ann Analysis of satellite and climatic Data
  • On The Probabillstic Interpretation of Area Based Fuzzy Land Cover mixing Proportions
  • Patterning of Community Changes in Benthic Macroinvertebrates Collected from urbanized Streams for the Short Time Prediction by Temporal Artificial Neuronal Networks
  • Neuronal network models of Phytoplankton Primary Production
  • Predicting Presence of Fish Species in the Seine River Basin Using Artificial Neuronal Networks
  • Elucidation and Prediction of Aquatic Ecosystem by Artificial Neuronal networks
  • Performance Comparison between Regression and Neuronal Network Models for Forecasting Pacific Sardine (Sardinops caeruleus)Biomass
  • A Comparison of Artificial Neuronal and Conventional Statistical Techniques for analyzing Environmental DataApplication of the Self Organizing Mapping and Fuzzy Clustering to Microsatellite Data: How to detect Genetic Structure in Brown Trout (Salmo Trutta) Populations
  • The Macroepidemiology of Parasite and Infectious Diseases: A comparative Study Using Artificial Neuronal Nets and Logistic Regressions
  • Evolutionarily Optimal Networks for Controlling Energy Allocation to Growth, Reproduction and repair in men and Women
  • Can Neuronal networks be Used in Data-Poor Situations?