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Time-Series Prediction and Applications - 16 Angebote vergleichen
Preise | 2017 | 2019 | 2020 |
---|---|---|---|
Schnitt | € 97,38 | € 106,04 | € 138,99 |
Nachfrage |
Time-Series Prediction and Applications
ISBN: 9783319545967 bzw. 3319545965, in Deutsch, Springer Shop, gebundenes Buch, neu.
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. Hard cover.
Time-Series Prediction and Applications
ISBN: 9783319545974 bzw. 3319545973, in Deutsch, Springer Shop, neu, E-Book, elektronischer Download.
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. eBook.
/ Bhattacharya | Time-Series Prediction and Applications | Springer GmbH | 2017
ISBN: 9783319545967 bzw. 3319545965, in Deutsch, Springer-Verlag GmbH, neu.
Time-Series Prediction and Applications (2017)
ISBN: 9783319545974 bzw. 3319545973, in Englisch, Springer, Springer, Springer, neu, E-Book, elektronischer Download.
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.
Time-series Prediction And Applications: A Machine Intelligence Approach
ISBN: 9783319545967 bzw. 3319545965, vermutlich in Englisch, neu.
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-seriesPrimarily 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.
Time-Series Prediction and Applications
ISBN: 9783319545967 bzw. 3319545965, in Deutsch, neu.
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-seriesPrimarily 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.
Time-Series Prediction and Applications (2017)
ISBN: 9783319545974 bzw. 3319545973, in Englisch, Springer, Springer, Springer, neu, E-Book, elektronischer Download.
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.
Time-Series Prediction and Applications (2017)
ISBN: 9783319545974 bzw. 3319545973, in Deutsch, Springer International Publishing, Taschenbuch, neu.
Time-Series Prediction and Applications (2017)
ISBN: 3319545965 bzw. 9783319545967, vermutlich in Englisch, Springer International Publishing, gebundenes Buch, neu.