Nikolaev / Iba Adaptive Learning of Polynomial Networks
2006
ISBN: 978-0-387-31240-8
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark
Genetic Programming, Backpropagation and Bayesian Methods
E-Book, Englisch, 316 Seiten, eBook
Reihe: Genetic and Evolutionary Computation
ISBN: 978-0-387-31240-8
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark
This book delivers theoretical and practical knowledge for developing algorithms that infer linear and non-linear multivariate models, providing a methodology for inductive learning of polynomial neural network models (PNN) from data. The text emphasizes an organized model identification process by which to discover models that generalize and predict well. The book further facilitates the discovery of polynomial models for time-series prediction.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
Inductive Genetic Programming.- Tree-Like PNN Representations.- Fitness Functions and Landscapes.- Search Navigation.- Backpropagation Techniques.- Temporal Backpropagation.- Bayesian Inference Techniques.- Statistical Model Diagnostics.- Time Series Modelling.- Conclusions.
