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IJAIA 2021 : International Journal of Artificial Intelligence & Applications | |||||||||||||||||||||||||||||||||||||||||||
Link: http://www.airccse.org/journal/ijaia/ijaia.html | |||||||||||||||||||||||||||||||||||||||||||
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Call For Papers | |||||||||||||||||||||||||||||||||||||||||||
International Journal of Artificial Intelligence & Applications (IJAIA) Citations, h-index, i10-index of IJAIAScope and TopicsThe International Journal of Artificial Intelligence & Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence & Applications (IJAIA). It is an international journal intended for professionals and researchers in all fields of AI for researchers, programmers, and software and hardware manufacturers. The journal also aims to publish new attempts in the form of special issues on emerging areas in Artificial Intelligence and applications. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Artificial Intelligence & applications. Topics of interest include, but are not limited to, the following: Topics of Interest
Paper SubmissionAuthors are invited to submit papers for this journal through Email: ijaiajournal@airccse.org or through Submission System.Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. Important Dates
Related JournalCurrent IssueNovember 2020, Volume 11, Number 5/6 Problem Decomposition and Information Minimization for the Global, Concurrent, On-line Validation of Neutron Noise Signals and Neutron Detector Operation Full Text Intelligent Portfolio Management via NLP Analysis of Financial 10-k Statements Full Text Object Sorting using Faster R-CNN Full Text Using Contextual Graphs as a Decision-making Tool in the Process of Hiring Candidates Full Text Automatic Transfer Rate Adjustment for Transfer Reinforcement Learning Full Text Answer Set Programming to Model Plan Agent Scenarios Full Text Editor In Chief
Associate Editors
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