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Advanced artificial intelligence in data science for Energy Informatics Systems (EIS)

Energy Informatics welcomes submissions to the new thematic series on 'Advanced artificial intelligence in data science for Energy Informatics Systems (EIS)'

Advanced analytical methods play an essential role in the age of big data. Many industries are making full use of big data after years of research and development, such as smart cities, public transportation, marketing campaigns, financial frauds detection, sports entertainment, and personal life. With the rapid development of smart grids, a lot of net metering and monitoring sensors have been deployed for collecting a large variety of data at an unbelievable granularity and volume. These vast data can be used to analyze the management mode of power consumption, enhance the safe operation control of the power grid, and improve the efficiency of the power grid. Therefore, it has become a significant challenge on how to manage and utilize the massive amounts of collected data in energy informatics systems.

Thanks to the complexity and abundance of data, artificial intelligence is playing a vital role in big data analytics. This special issue is focused on the application of advance artificial intelligence and data science techniques for a better understanding of the energy informatics system. We encourage the researchers to publish their original papers and visionary surveys related to the state-of-the-art methodology, technologies, algorithms, and real world, with a particular emphasis on a pilot study on how the energy informatics system benefits from the use of artificial intelligence and data science.

Topics of interest include, but are not limited to:

  • New theories and application of machine learning for EIS
  • Design, development and application of deep learning for EIS
  • Artificial intelligence for EIS
  • Data-driven analytics for EIS
  • Cloud and edge computing for EIS
  • Artificial intelligence for EIS security
  • Data science and big data for EIS analysis
  • Artificial intelligence and big data management for EIS 
  • Data mining for EIS
  • AI and data science for cybersecurity for EIS

Deadline for submissions:  
30 June 2021

Guest editors

Prof. Yun Lin, Harbin Engineering University, China
Dr. Joey Tianyi Zhou, Institute of High Performance Computing, A*STAR, Singapore
Prof. Ya Tu, Harbin Engineering University, China
Prof. Yan Zhang, University of Oslo, Norway
Prof. Shiwen Mao, Auburn University, USA

Submission Instructions
Before submitting your manuscript, please ensure you have carefully read the submission guidelines for Energy Informatics. The complete manuscript should be submitted through the Energy Informatics submission system. To ensure that you submit to the correct thematic series please select the appropriate thematic series in the drop-down menu upon submission. In addition, indicate within your cover letter that you wish your manuscript to be considered as part of the thematic series ‘Towards a critical perspective on data literacy in higher education. Emerging practices and challenges’. All submissions will undergo rigorous peer review and accepted articles will be published within the journal as a collection.

Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the journal’s collections page. 

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). 

The Article Processing Charge (APC) for publication in this journal is listed at Fees and funding. Submitted papers should be well formatted and use good English. 

Submissions will also benefit from the usual advantages of open access publication:

Rapid publication: Online submission, electronic peer review and production make the process of publishing your article simple and efficient

High visibility and international readership in your field: Open access publication ensures high visibility and maximum exposure for your work - anyone with online access can read your article

No space constraints: Publishing online means unlimited space for figures, extensive data and video footage

Authors retain copyright, licensing the article under a Creative Commons license: articles can be freely redistributed and reused as long as the article is correctly attributed

Annual Journal Metrics

  • Speed
    30.3 days to first decision for reviewed manuscripts only
    30.7 days to first decision for all manuscripts
    55.3 days from submission to acceptance
    34 days from acceptance to publication

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