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Deep Learning in Multi-step Prediction of Chaotic Dynamics - From Deterministic Models to Real-World Systems (Paperback, 1st ed. 2021) Loot Price: R1,560
Discovery Miles 15 600
Deep Learning in Multi-step Prediction of Chaotic Dynamics - From Deterministic Models to Real-World Systems (Paperback, 1st...

Deep Learning in Multi-step Prediction of Chaotic Dynamics - From Deterministic Models to Real-World Systems (Paperback, 1st ed. 2021)

Matteo Sangiorgio, Fabio Dercole, Giorgio Guariso

Series: SpringerBriefs in Applied Sciences and Technology

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Loot Price R1,560 Discovery Miles 15 600 | Repayment Terms: R146 pm x 12*

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The book represents the first attempt to systematically deal with the use of deep neural networks to forecast chaotic time series. Differently from most of the current literature, it implements a multi-step approach, i.e., the forecast of an entire interval of future values. This is relevant for many applications, such as model predictive control, that requires predicting the values for the whole receding horizon. Going progressively from deterministic models with different degrees of complexity and chaoticity to noisy systems and then to real-world cases, the book compares the performances of various neural network architectures (feed-forward and recurrent). It also introduces an innovative and powerful approach for training recurrent structures specific for sequence-to-sequence tasks. The book also presents one of the first attempts in the context of environmental time series forecasting of applying transfer-learning techniques such as domain adaptation.

General

Imprint: Springer Nature Switzerland AG
Country of origin: Switzerland
Series: SpringerBriefs in Applied Sciences and Technology
Release date: February 2022
First published: 2021
Authors: Matteo Sangiorgio • Fabio Dercole • Giorgio Guariso
Dimensions: 235 x 155mm (L x W)
Format: Paperback
Pages: 104
Edition: 1st ed. 2021
ISBN-13: 978-3-03-094481-0
Categories: Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematical modelling
Books > Science & Mathematics > Physics > Thermodynamics & statistical physics > Statistical physics
Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN: 3-03-094481-6
Barcode: 9783030944810

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