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. Key Features • It is a self-contained and integrated monograph. Both algorithms and applications are included in the book • ANNs in the book are treated in mathematical way but not in machine-learning way. Mathematical principles of ANNs are discussed in the book, which will help readers understand the similarities and differences between ANNs modeling and conventional models in ecology • Includes the most recent advances in ecological applications of ANNs • Matlab codes are presented for easy use by readers • A new ecological discipline, i.e., computational ecology, is proposed in the book

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