Dynamic Fuzzy Machine Learning

 
 
De Gruyter (Verlag)
  • erschienen im Dezember 2017
 
  • Buch
  • |
  • Hardcover
  • |
  • 337 Seiten
978-3-11-051870-2 (ISBN)
 
Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of big data, cloud computing, the Internet of Things, and quantum information. At present, the processing of this kind of data is not very mature. The authors carried out more than 20 years of research, and show in this book their most important results. The seven chapters of the book are devoted to key topics such as dynamic fuzzy machine learning models, dynamic fuzzy self-learning subspace algorithms, fuzzy decision tree learning, dynamic concepts based on dynamic fuzzy sets, semi-supervised multi-task learning based on dynamic fuzzy data, dynamic fuzzy hierarchy learning, examination of multi-agent learning model based on dynamic fuzzy logic. This book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artificial intelligence, machine learning, automation, data analysis, mathematics, management, cognitive science, and finance. It can be also used as the basis for teaching the principles of dynamic fuzzy learning.
80 s/w Abbildungen
1. Auflage 2018
  • Englisch
  • Berlin
  • |
  • Deutschland
  • Für Beruf und Forschung
  • geheftet
  • |
  • Gewebe-Einband
  • Höhe: 245 mm
  • |
  • Breite: 180 mm
  • |
  • Dicke: 24 mm
  • 783 gr
978-3-11-051870-2 (9783110518702)
3110518708 (3110518708)
weitere Ausgaben werden ermittelt

Fanzhang Li, Zhang Li, Zhang Zhao, Soochow University, Suzhou, China


Sofort lieferbar

129,95 €
inkl. 7% MwSt.
in den Warenkorb

Abholung vor Ort? Sehr gerne!