Artificial Neuronal Networks

In this book, an easily understandable account of modelling methods with artificial neuronal networks for practical applications in ecology and evolution is provided. Special features include examples of applications using both supervised and unsupervised training, comparative analysis of artificial neural networks and conventional statistical methods, and proposals to deal with poor datasets. Extensive references and a large range of topics make this book a useful guide for ecologists, evolutionary ecologists and population geneticists.

Unique approach of modelling methods with artificial neuronal networks Practical applications in Ecology and Evolution Numerous case studies

Inhalt
I Introduction.- 1 Neuronal Networks: Algorithms and Architectures for Ecologists and Evolutionary Ecologists.- II Artificial Neuronal Networks in Landscape Ecology and Remote Sensing.- 2 Predicting Ecologically Important Vegetation Variables from Remotely Sensed Optical/Radar Data Using Neuronal Networks.- 3 Soft Mapping of Coastal Vegetation from Remotely Sensed Imagery with a Feed-Forward Neuronal Network.- 4 Ultrafast Estimation of Neotropical Forest DBH Distributions from Ground Based Photographs Using a Neuronal Network.- 5 Normalized Difference Vegetation Index Estimation in Grasslands of Patagonia by ANN Analysis of Satellite and Climatic Data.- 6 On the Probabilistic Interpretation of Area Based Fuzzy Land Cover Mixing Proportions.- III Artificial Neuronal Networks in Population, Community and Ecosystem Ecology.- 7 Patterning of Community Changes in Benthic Macroinvertebrates Collected from Urbanized Streams for the Short Time Prediction by Temporal Artificial Neuronal Networks.- 8 Neuronal Network Models of Phytoplankton Primary Production.- 9 Predicting Presence of Fish Species in the Seine River Basin Using Artificial Neuronal Networks.- 10 Elucidation and Prediction of Aquatic Ecosystems by Artificial Neuronal Networks.- 11 Performance Comparison between Regression and Neuronal Network Models for Forecasting Pacific Sardine (Sardinops caeruleus) Biomass.- 12 A Comparison of Artificial Neuronal Network and Conventional Statistical Techniques for Analyzing Environmental Data.- IV Artificial Neuronal Networks in Genetics and Evolutionary Ecology.- 13 Application of the Self-Organizing Mapping and Fuzzy Clustering to Microsatellite Data: How to Detect Genetic Structure in Brown Trout (Salmo trutta) Populations.- 14 The Macroepidemiology of Parasitic and Infectious Diseases: A Comparative Study Using Artificial Neuronal Nets and Logistic Regressions.- 15 Evolutionarily Optimal Networks for Controlling Energy Allocation to Growth, Reproduction and Repair in Men and Women.- V Perspectives.- 16 Can Neuronal Networks be Used in Data-Poor Situations?.