Evolutionary Approach to Machine Learning and Deep Neural Networks: Neuro-Evolution and Gene Regulatory Networks

-15% su kodu: ENG15
215,97 
Įprasta kaina: 254,08 
-15% su kodu: ENG15
Kupono kodas: ENG15
Akcija baigiasi: 2025-03-03
-15% su kodu: ENG15
215,97 
Įprasta kaina: 254,08 
-15% su kodu: ENG15
Kupono kodas: ENG15
Akcija baigiasi: 2025-03-03
-15% su kodu: ENG15
2025-02-28 254.0800 InStock
Nemokamas pristatymas į paštomatus per 11-15 darbo dienų užsakymams nuo 10,00 

Knygos aprašymas

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.

Informacija

Autorius: Hitoshi Iba
Leidėjas: Springer Nature Singapore
Išleidimo metai: 2018
Knygos puslapių skaičius: 260
ISBN-10: 9811301999
ISBN-13: 9789811301995
Formatas: 241 x 160 x 20 mm. Knyga kietu viršeliu
Kalba: Anglų

Pirkėjų atsiliepimai

Parašykite atsiliepimą apie „Evolutionary Approach to Machine Learning and Deep Neural Networks: Neuro-Evolution and Gene Regulatory Networks“

Būtina įvertinti prekę

Goodreads reviews for „Evolutionary Approach to Machine Learning and Deep Neural Networks: Neuro-Evolution and Gene Regulatory Networks“