Optimization of Deep Learning in the Perspective of Sustainability
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".
Deadline for manuscript submissions: closed (30 August 2023) | Viewed by 8214
Special Issue Editors
Interests: deep learning; big data; artificial intelligence; image recognition; financial statistics
Special Issues, Collections and Topics in MDPI journals
Interests: data mining; machine/deep learning; big data analysis in healthcare
Special Issues, Collections and Topics in MDPI journals
Interests: big data; machine learning; artificial intelligence; business analytics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the advent of novel technologies such as mobile technology, IOT, and sensors due to the advancement of ICT technology, organizations are now faced with an environment where they create and use huge amounts of various types of big data.
While traditional data analysis focused on hypothesis verification based on deriving correlations between structured data, in the era of big data, the procedure of discovering and verifying hypotheses, taking into account not only structured data, but also unstructured data, is becoming more common.
Artificial intelligence is drawing attention as the most useful tool for such big data analyses, and, in particular, novel technology based on deep learning is being developed at a rapid pace. Novel deep learning technologies can be applied to various fields, providing key solutions to problems that humans cannot solve, and are recognized as important in academia and industry.
Therefore, deep learning technology has become an essential element in securing sustainable competitiveness for various stakeholders, and is an interesting subject to many researchers.
This Special Issue covers an approach to creative analytical models and generating innovative results through a big data analysis based on the optimization of deep learning technologies.
Topics of interest for this Special Issue include (but are not limited to):
- Artificial intelligence for sustainability;
- Business intelligence;
- Customer big data analytics;
- Deep learning approach in healthcare;
- Deep learning for financial market prediction;
- Deep learning application for text mining;
- Image reconstruction technology with deep learning;
- Novel methods for big data analytics;
- Optimization of deep learning for sustainability.
We look forward to receiving your contributions.
Dr. Jae Joon Ahn
Dr. Sukjun Lee
Dr. Jaeyun Kim
Guest Editors
Manuscript Submission Information
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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. Sustainability 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 2400 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
- big data analytics
- deep learning
- machine learning
- sustainability
- text mining
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