Open access peer-reviewed Edited Volume

Dynamic Data Assimilation - Beating the Uncertainties

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Academic Editor

Dinesh Harkut
Dinesh Harkut

Prof Ram Meghe College of Engineering & Management, Badnera-Amravati, India,
India

Published28 October 2020

Doi10.5772/intechopen.87789

ISBN978-1-83968-084-7

Print ISBN978-1-83968-083-0

eBook (PDF) ISBN978-1-83968-085-4

Copyright year2020

Number of pages118

Data assimilation is a process of fusing data with a model for the singular purpose of estimating unknown variables. It can be used, for example, to predict the evolution of the atmosphere at a given point and time. This book examines data assimilation methods including Kalman filtering, artificial intelligence, neural networks, machine learning, and cognitive computing.

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Table of Contents

Open access  chapters

554
914
3
5. Kalman Filtering Applied to Induction Motor State Estimation

By Yassine Zahraoui and Mohamed Akherraz

1,088
3
6. Data Processing Using Artificial Neural Networks

By Wesam Salah Alaloul and Abdul Hannan Qureshi

2,078
18

IMPACT OF THIS BOOK AND ITS CHAPTERS

5,943 Total Chapter Downloads

27 Crossref Citations

5 Web of Science Citations

48 Dimensions Citations

4 Altmetric Score

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