Due to the complexity and non-linearity of most ecological problems, artificial neural networks (ANNs) have attracted attention from ecologists and environmental scientists in recent years. As these networks are increasingly being used in ecology for modeling, simulation, function approximation, prediction, classification and data mining, this unique and self-contained book will be the first comprehensive treatment of this subject, by providing readers with overall and in-depth knowledge on algorithms, programs, and applications of ANNs in ecology. Moreover, a new area of ecology, i.e., computational ecology, is proposed and its scopes and objectives are defined and discussed.

Computational Ecology consists of two parts: the first describes the methods and algorithms of ANNs, interpretability and mathematical generalization of neural networks, Matlab neural network toolkit, etc., while the second provides case studies of applications of ANNs in ecology, Matlab codes, and comparisons of ANNs with conventional methods. This publication will be a valuable reference for research scientists, university teachers, graduate students and high-level undergraduates in the areas of ecology, environmental sciences, and computational science.

Contents:
Artificial Neural Networks: Principles, Theories and Algorithms:
Feedforward Neural Networks
Linear Neural Networks
Radial Basis Function Neural Networks
BP Neural Network
Self-Organizing Neural Networks
Feedback Neural Networks
Design and Customization of Artificial Neural Networks
Learning Theory, Architecture Choice and Interpretability of Neural Networks
Mathematical Foundations of Artificial Neural Networks
Matlab Neural Network Toolkit
Applications of Artificial Neural Networks in Ecology:
Dynamic Modeling of Survivor Process
Simulation of Plant Growth Process
Simulation of Food Intake Dynamics
Species Richness Estimation and Sampling Data Documentation
Modeling Arthropod Abundance from Plant Composition of Grassland Community
Pattern Recognition and Classification of Ecosystems and Functional Groups
Modeling Spatial Distribution of Arthropods
Risk Assessment of Species Invasion and Establishment
Prediction of Surface Ozone
Modeling Dispersion and Distribution of Oxide and Nitrate Pollutants
Modeling Terrestrial Biomass

Readership: Research scientists, university teachers, graduate students and high-level undergraduates in the area of ecology, environmental sciences and computational science.