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Machine Learning Algorithms under Uncertainty: Real-world Systems

Machine Learning Algorithms under Uncertainty: Real-world Systems

Journal
Impact Score 4.12

OFFICIAL WEBSITE

Special Issue Information

Submission Deadline: 30-07-2021
Journal Impact Score: 4.12
Journal Name: International Journal of Fuzzy Systems
Publisher: International Journal of Fuzzy Systems
Journal & Submission Website: https://www.springer.com/journal/40815

Special Issue Call for Papers

Special Issue Editors

Dr. Ali Ahmadian (Lead Guest Editor)University Mediterranea of Reggio Calabria, Reggio Calabria, Italy

Dr. Ahmad Taher AzarPrince Sultan University, Saudi Arabia

Dr. Soheil Salahshour|Bahcesehir University, Turkey

Dr. Shun-Feng SuChair Professor, EE, NTUST, Taiwan

Special Issue Information

Due to the existence of uncertainty in the structure of modelling, uncertainties play a major role in the dynamical processes. So, appearance of such uncertainties in the data is inevitable, and consequently, applying uncertain differential equations is a natural way to respond to the situations. Because of the presence of uncertainty, obtaining an exact solution for such systems is not applicable. For responding to this essential restriction, several numerical methods were applied to derive the approximate solutions. However, working with large systems need to be applied some adaptive approach like using machine learning algorithms.

Machine learning (ML) algorithms focus on separating hyperplane to maximizes the margin between two classes in this space.  For real-world applications, the input of the system should be considered under uncertainty. For such restriction in comparison to the deterministic ML, we need to provide the membership with uncertainty to each input point of ML and reformulates ML into uncertain ML (FML). Using this realization, the ML algorithms will be more applicable, global minima of the original problem will be determined better, as well.

This special issue will provide a systematic overview and state-of-the-art research in the field of Intelligent Decision systems with machine learning applications and will outline new and important developments in fundamentals, approaches, models, methodologies, and applications in this area.

Specific topics of interest include (but are not limited to):

Manuscript Submission Information

All manuscripts must be submitted through the manuscripts system at https://www.editorialmanager.com/ijfs/default.aspx 

Please select the designated special issue (SI) in the additional information Questionnaire (the fourth step). 

A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page.

Timetable

Submission Deadline: 30 July 2021Authors Notification: 20 September 2021Revised Papers Deadline: 25 December 2021Final Notification: 31 March 2022

Closed Special Issues

Publisher
Journal Details
Closing date
G2R Score
Machine Learning Algorithms under Uncertainty: Real-world Systems

Machine Learning Algorithms under Uncertainty: Real-world Systems

International Journal of Fuzzy Systems
Closing date: 30-07-2021 G2R Score: 4.12
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Closing date: 31-12-2020 G2R Score: 4.12
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Closing date: 30-11-2020 G2R Score: 4.12
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Applications of Intelligent and Fuzzy Theory in Data Science

International Journal of Fuzzy Systems
Closing date: 30-09-2020 G2R Score: 4.12
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Fuzzy System in Data mining and Knowledge Discovery: Modeling and Application

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Closing date: 30-03-2016 G2R Score: 4.12
Advances in Evolutionary Fuzzy Systems

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Closing date: 15-09-2015 G2R Score: 4.12