Time-Series Prediction and Applications: A Machine Intelligence Approach: 127 (Intelligent Systems Reference Library, 127) - Tapa dura

Libro 96 de 188: Intelligent Systems Reference Library

Konar, Amit; Bhattacharya, Diptendu

 
9783319545967: Time-Series Prediction and Applications: A Machine Intelligence Approach: 127 (Intelligent Systems Reference Library, 127)
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ISBN 10: 3319545965 ISBN 13: 9783319545967
Editorial: Springer, 2017

Sinopsis

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.

"Sinopsis" puede pertenecer a otra edición de este libro.

De la contraportada

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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2017
Idioma
Inglés
ISBN 10 
3319545965
ISBN 13 
9783319545967
Encuadernación
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Número de edición
1
Número de páginas
262
Contacto del fabricante
ProductSafety@springernature.com
ProductSafety@springernature.com

Poststr. 9
Darmstadt
64293
Alemania

Otras ediciones populares con el mismo título

9783319854359: Time-Series Prediction and Applications: A Machine Intelligence Approach: 127 (Intelligent Systems Reference Library)

Edición Destacada

ISBN 10:  3319854356 ISBN 13:  9783319854359
Editorial: Springer, 2018
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