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Machine Learning and Artificial Intelligence with Applications
This special issue belongs to the section “Information Applications“.
Special Issue Information
Dear Colleagues,
Artificial Intelligence (AI) and Machine Learning (ML) techniques have become increasingly prominent in scientific disciplines such as computer vision, natural language processing, and speech recognition. These methodologies are now being implemented across various domains, including industrial, energy, vehicular technologies, financial, healthcare, manufacturing, transportation, agricultural, and logistic systems. This Special Issue aims to report on recent advances in state-of-the-art research on artificial intelligence and machine learning fields. Further, this Special Issue also focuses on the development of novel AI and ML algorithms for engineering applications.
The research domains may include (but are not limited to):
- Neural architecture search;
- AutoML;
- Evolutionary deep learning;
- Hyperparameter optimization;
- Deep neuroevolution;
- Deep reinforcement learning;
- AI/ML algorithms for Cloud computing;
- AI/ML algorithms for communication and sensing;
- AI/ML algorithms for smart energy applications to smart cities;
- AI/ML algorithms for wireless IoT;
- AI/ML algorithms for e-Governance, socio-political, and economic systems.
Dr. Jae-Mo Kang
Dr. Vikas Palakonda
Guest Editors
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 250 words) can be sent to the Editorial Office for assessment.
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. Information is an international peer-reviewed open access monthly 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 1800 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
- machine learning
- deep learning
- reinforcement learning
- evolutionary computation
- optimization
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