Machine Learning and Deep
Learning for Time Series Processing and Analysis: Theories,
Techniques and Applications
The fast development of various time-dependent services (e.g.,
monitoring of physical, social and financial phenomena) and techniques (e.g.,
sensor devices and Internet of Thing (IoT)) has produced massive data captured
over the course of time, called time series data. As time series data becomes
more common and available, time series data processing and analysis are
increasingly important. In the Big Data era, the variety, volume and dimension
of time series data increase tremendously. In the past several years, some
machine learning (ML) and deep learning (DL) models have been applying for the
processing and analysis of big time series data because they have drastically
outperformed traditional approaches for dealing with time series data. This
book will go to great depth concerning the fast-growing topic of theories,
techniques and approaches of machine learning and deep learning for time series
data processing and analysis.
Specific topics of
interest of this book include but are not limited to the following.
·
Time series modelling with ML and DL
·
Time series data compression and dimensionality
reduction with ML and DL
·
Heterogeneous time series data fusion with ML and
DL
·
Anomaly detection in time series data with ML and
DL
·
ML and DL for time series forecasting
·
Time series data clustering and classification with
ML and DL
·
Time series data motifs and pattern mining with ML
and DL
·
Time series data management with ML and DL
·
Interpretable ML and DL models for time series data
analysis
·
ML and DL models for time series data privacy and
security
·
ML and DL for knowledge extraction, representation
and reasoning in time series data
·
ML and DL with semantics for time series data
·
ML and DL models for novel applications of time series
data
Authors are invited to
submit their chapters electronically to ruizhe_ma@uml.edu. For details on how to prepare
the manuscripts and style files refer to the instruction page for authors
https://www.springer.com/gp/authors-editors/book-authors-editors/manuscript-preparation/5636
This page also includes the
latex macro packages and further instructions.
Authors should submit their
original work that must not be submitted or currently under consideration for
publication anywhere.
Full chapter submission:
July 31, 2021
First Decision: September
30, 2021
Revision: October
31, 2021
Final Decision: November
30, 2021
Camera-ready: December
20, 2021
Any questions about this book, please feel free to
contact
Ruizhe
Ma, PhD & Assistant
Professor
Department of Computer Science
University of Massachusetts Lowel
Lowell, USA
e-mail: ruizhe_ma@uml.edu