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 scope 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 advanced-level undergraduates in the areas of ecology, environmental sciences, and computational sciences.
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Dr WenJun Zhang is an ecologist. He graduated from Northwestern Agricultural University, China, in 1984, and obtained his PhD degree in 1993. Dr Zhang was a postdoctoral fellow of Sun Yat-Sen University, China, during 1994 to 1996, and postdoctoral fellow and project scientist of International Rice Research Institute during 1997 to 2000. He was a visiting scientist to University of Arizona, USA (1996) and Wageningen University. The Netherlands (2002). Dr Zhang has published many papers and books. He is now working on ecology and environmental sciences.
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.
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