Time-Series Prediction and Applications - 8 Angebote vergleichen
| Preise | 2018 | 2019 | 2020 |
|---|---|---|---|
| Schnitt | € 145,06 | € 132,28 | € 149,99 |
| Nachfrage |
1
Time-Series Prediction and Applications
~EN PB NWISBN: 9783319854359 bzw. 3319854356, vermutlich in Englisch, Springer Shop, Taschenbuch, neu.
Lieferung aus: Vereinigte Staaten von Amerika, Lagernd, zzgl. Versandkosten.
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. Soft cover.
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. Soft cover.
2
/ Bhattacharya | Time-Series Prediction and Applications | Springer | Softcover reprint of the original 1st ed. 2017 | 2018
~EN PB NWISBN: 9783319854359 bzw. 3319854356, vermutlich in Englisch, Springer, Taschenbuch, 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.
3
Time-series Prediction And Applications: A Machine Intelligence Approach
~EN NWISBN: 9783319854359 bzw. 3319854356, vermutlich in Englisch, neu.
Lieferung aus: Kanada, Lagernd, zzgl. Versandkosten.
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.
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.
4
Time-Series Prediction and Applications (2017)
~EN PB NW RPISBN: 3319854356 bzw. 9783319854359, vermutlich in Englisch, Springer International Publishing, Taschenbuch, neu, Nachdruck.
Time-Series Prediction and Applications ab 149.99 € als Taschenbuch: A Machine Intelligence Approach. Softcover reprint of the original 1st ed. 2017. Aus dem Bereich: Bücher, Wissenschaft, Technik,.
5
Time-Series Prediction and Applications (2017)
~EN PB NW RPISBN: 3319854356 bzw. 9783319854359, vermutlich in Englisch, Taschenbuch, neu, Nachdruck.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
6
Time-Series Prediction and Applications (2017)
DE PB NW RPISBN: 3319854356 bzw. 9783319854359, in Deutsch, Taschenbuch, neu, Nachdruck.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
7
Time-Series Prediction and Applications (2018)
~EN HC NW RPISBN: 9783319854359 bzw. 3319854356, vermutlich in Englisch, gebundenes Buch, neu, Nachdruck.
Lieferung aus: Deutschland, Next Day, Versandkostenfrei.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
8
Time-Series Prediction and Applications
DE NWISBN: 9783319854359 bzw. 3319854356, in Deutsch, Springer Nature, neu.
Lieferung aus: Deutschland, Lagernd.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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