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Application of Machine Learning and Data Mining in Electrical Engineering 2021

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: closed (30 April 2021) | Viewed by 542

Special Issue Editor


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Guest Editor
Opus College of Engineering, Marquette University, Milwaukee, WI 53233, USA
Interests: machine learning; data mining; signal processing; dynamical systems; chaos
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Artificial Intelligence and Machine Learning have existed as fields of study since the 1950s, experiences rises and falls in interest. We now are at a new high level of interest in these areas with many novel applications of machine learning. With Electrical Engineering systems generating large amounts of data, we can apply data mining to discover new relationships in these systems. With the advent of deep neural networks, we can learn new mappings between inputs and output of these systems. This Special Issue explores the latest findings in applying machine learning to Electrical Engineering systems. We welcome novel applications of machine learning and data mining in areas of electrical engineering, such as antennas, communications, controls, devices, hardware design, power and energy, sensor systems, and signal processing.

Dr. Richard J. Povinelli
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence
  • data mining
  • deep learning
  • electrical engineering
  • machine learning

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Published Papers

There is no accepted submissions to this special issue at this moment.
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