Computing Network Model for Intelligent Systems: Hybrid of Neural Networks, Multi-knowledge, Fuzzy Logic, Rough Set, and Bayesian Classifier - Qingxiang Wu - Libros - VDM Verlag Dr. Müller - 9783639225600 - 8 de enero de 2010
En caso de que portada y título no coincidan, el título será el correcto

Computing Network Model for Intelligent Systems: Hybrid of Neural Networks, Multi-knowledge, Fuzzy Logic, Rough Set, and Bayesian Classifier


Recibe un correo electrónico cuando el artículo esté disponible
¿Tienes un perfil? Iniciar sesión
Añadir a tu lista de deseos de iMusic

Scientists mimicked birds and eventually created airplanes using integration of biological principles and modern science and technology. In recent decades scientists have been trying to simulate intelligence in the brain, in which huge number of neurons forms powerful computing networks to perform intelligent behaviours. This book presented a framework of computing network models for artificial intelligent systems to mimic intelligent behaviours. The models are inspired from some biological principles, and furthermore they have been enhanced using hybrid of current artificial intelligent techniques such as machine learning, neural networks, multi-knowledge, fuzzy logic, rough set, Bayes classifier, and evidence reasoning theory. The key idea of the book is to encourage scientists to take more biological findings to build artificial intelligent systems. More importantly biologically inspired models should be extended to combine current artificial intelligent techniques to achieve high level intelligence in some specific aspects. The book presents a demonstration of the effort in implementation of intelligent behaviours using computing networks.

Medios de comunicación Libros     Paperback Book   (Libro con tapa blanda y lomo encolado)
Publicado 8 de enero de 2010
ISBN13 9783639225600
Editores VDM Verlag Dr. Müller
Páginas 292
Dimensiones 150 × 220 × 10 mm   ·   430 g
Lengua Inglés  

Mere med samme udgiver