Übersicht			Auf mobile öffnen

Lieferstatus:	Auf Bestellung (Lieferzeit unbekannt)
Veröffentlichung:	April 2017
Genre:	Naturwissensch., Medizin, Technik
	Artificial Intelligence / B / Computational Intelligence / Computational Mathematics and Numerical Analysis / Computer mathematics / engineering / Numerical analysis / Numerische Mathematik
ISBN:	9783319545967
EAN-Code:	9783319545967
Verlag:	Springer EN
Einband:	Gebunden
Sprache:	English
Serie:	#127 - Intelligent Systems Reference Library
Dimensionen:	H 235 mm / B 155 mm / D
Gewicht:	5148 gr
Seiten:	242
Illustration:	XVIII, 242 p. 69 illus., 13 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen
Zus. Info:	EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025.
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications. It also proposes new uncertainty management techniques in an economic time-series using type-2 fuzzy sets for prediction of the time-series at a given time point from its preceding value in fluctuating business environments. It employs machine learning to determine repetitively occurring similar structural patterns in the time-series and uses stochastic automaton to predict the most probabilistic structure at a given partition of the time-series. Such predictions help in determining probabilistic moves in a stock index time-series Primarily written for graduate students and researchers in computer science, the book is equally useful for researchers/professionals in business intelligence and stock index prediction. A background of undergraduate level mathematics is presumed, although not mandatory, for most of the sections. Exercises with tips are provided at the end of each chapter to the readers' ability and understanding of the topics covered.