[AISWorld] Special Issue: Machine Learning in Data Analytics and Prediction

[Rogério Luís de Carvalho Costa]

------------------------------------------------------------------------
*Our apologies if you receive multiple copies of this call
*Please forward to anyone who might be interested*
------------------------------------------------------------------------

*******************************************************************************

Dear Colleagues,

We are pleased to announce a new Special Issue, "Machine Learning in Data Analytics and Prediction", which aims to allow researchers and practitioners from different research areas to share their experiences in developing state-of-the-art machine learning-based analytics and prediction solutions through new methods, novel architectures and systems, and real-world applications that could benefit from the proposed solutions. Researchers are invited to submit research works describing innovative methods, algorithms, and platforms covering any facets of machine learning in data analytics and prediction. Application papers detailing industrial implementations, design, and deployment experience reports on how machine learning can solve relevant practical problems related to analytics and prediction are also welcome.

We welcome technical, experimental, and methodological manuscripts, as well as contributions to applied data science, that address any topics on advances in machine learning-based analytics and prediction methods, systems, and applications, including data and integration, deep neural networks, explainable AI, computational intelligence, and concept drift management, in fields like management, business, engineering, computer science, and physical, social, and life sciences.

Application scenarios of interest include, but are not limited to:

  *
Cybersecurity and privacy maintenance.
  *
Management and marketing.
  *
Economics, finance, and accounting.
  *
Life sciences and healthcare.
  *
Internet of Things (IoT).
  *
Energy and Industry 4.0.
  *
Business and societal challenges.
  *
Environmental sustainability.

Deadline for manuscript submissions: 15 November 2024
Special issue web site: https://www.mdpi.com/journal/electronics/special_issues/machinelearning_dataanalytics
Guest Editors:

  *
Prof. Dr. Rogério Luís de Carvalho Costa, CIIC, ESTG, Polytechnic of Leiria, Portugal
  *
Prof. Dr. Leonel Filipe Simões Santos, CIIC, ESTG, Polytechnic of Leiria, Portugal
  *
Prof. Dr. Carlos Rabadão, CIIC, ESTG, Polytechnic of Leiria, Portugal

Message from the Editor-in-Chief:
Electronics is a multidisciplinary journal designed to appeal to a diverse audience of research scientists, practitioners, and developers in academia and industry. The journal is devoted to fast publication of latest technological breakthroughs, cutting-edge developments, and timely reviews of current and emerging technologies related to the broad field of electronics. Experimental and theoretical results are published as regular peer-reviewed articles or as articles within Special Issues guest-edited by leading experts in selected topics of interest.
Author Benefits:

  *
Open Access: free for readers, with article processing charges (APC)<https://www.mdpi.com/journal/electronics/apc> paid by authors or their institutions.
  *
High Visibility: indexed within Scopus, SCIE (Web of Science), CAPlus/SciFinder, Inspec, and other databases.
  *
Journal Rank: JCR - Q2(Electrical and Electronic Engineering) CiteScore - Q2 (Electrical and Electronic Engineering)