Evolutionary Approach to Machine Learning and Deep Neural Networks

Neuro-Evolution and Gene Regulatory Networks

Autor: Hitoshi Iba

Jazyk:

Väzba: Pevná

Vydavateľ: Springer Verlag, Singapore

Dostupnosť: Skladom u dodávateľa

Odosielame za 10-13 dní

150.00 €

This book provides theoretical and practical knowledge about a methodology for evolutionary algorith...

Informácie o knihe

Autor

Hitoshi Iba

Jazyk

Angličtina

Väzba

Kniha - Pevná

Vydalo

2018

Stránok

245

EAN

9789811301995

ISBN

9811301999

Enbook ID

19193000

Vydavateľ

Springer Verlag, Singapore

Hmotnosť

559

Rozmery

155 x 235 x 22

Kompletný popis

This book provides theoretical and practical knowledge about a methodology for evolutionary algorithm-based search strategy with the integration of several machine learning and deep learning techniques. These include convolutional neural networks, Gröbner bases, relevance vector machines, transfer learning, bagging and boosting methods, clustering techniques (affinity propagation), and belief networks, among others. The development of such tools contributes to better optimizing methodologies. Beginning with the essentials of evolutionary algorithms and covering interdisciplinary research topics, the contents of this book are valuable for different classes of readers: novice, intermediate, and also expert readers from related fields. Following the chapters on introduction and basic methods, Chapter 3 details a new research direction, i.e., neuro-evolution, an evolutionary method for the generation of deep neural networks, and also describes how evolutionary methods are extended in combination with machine learning techniques. Chapter 4 includes novel methods such as particle swarm optimization based on affinity propagation (PSOAP), and transfer learning for differential evolution (TRADE), another machine learning approach for extending differential evolution. The last chapter is dedicated to the state of the art in gene regulatory network (GRN) research as one of the most interesting and active research fields. The author describes an evolving reaction network, which expands the neuro-evolution methodology to produce a type of genetic network suitable for biochemical systems and has succeeded in designing genetic circuits in synthetic biology. The author also presents real-world GRN application to several artificial intelligent tasks, proposing a framework of motion generation by GRNs (MONGERN), which evolves GRNs to operate a real humanoid robot.

Mohlo by vás zaujímať

Zákazníci, ktorí si kúpili túto knihu, kúpili tiež

Najčastejšie vyhľadávané

Categories

Authors

Publishers

Produkty

Produkty

Najčastejšie vyhľadávané

Categories

Authors

Publishers

Produkty

Produkty

Evolutionary Approach to Machine Learning and Deep Neural Networks

Neuro-Evolution and Gene Regulatory Networks

Informácie o knihe

Kompletný popis

Mohlo by vás zaujímať

Zákazníci, ktorí si kúpili túto knihu, kúpili tiež