Application of Machine Learning and Data Mining in Electrical Engineering
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".
Deadline for manuscript submissions: closed (10 October 2019) | Viewed by 65098
Special Issue Editors
Interests: machine learning; data mining; signal processing; dynamical systems; chaos
Special Issues, Collections and Topics in MDPI journals
Interests: machine learning applied to optimization in multicore processors and datacenters; embedded systems; environment monitoring; IoT security
Special Issues, Collections and Topics in MDPI journals
Interests: Computer vision, Robotic vision and vision for autonomous vehicles, Wireless sensor/camera networks, Vision-based distributed target tracking, Object detection and recognition
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
Dr. Cristinel Ababei
Dr. Henry Medeiros
Guest Editors
Manuscript Submission Information
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Keywords
- artificial intelligence
- data mining
- deep learning
- electrical engineering
- machine learning
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