Special Issue "Analysis, Processing, and Applications of Fuzzy System and Deep Learning"

Submission Deadline: 30 July 2022 (closed)
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Guest Editors
Dr. Seongsoo Cho, Soongsil University, Korea.
Dr. Emad Alsusa, University of Manchester, U.K.
Dr. YoungMan Kwon, Eulji University, Korea.


Fuzzy systems are one of the most exciting fields of computing today Over the past decades, fuzzy logic has become a solid part of everyday life and has been successfully used to solve real-world problems.

The applications of fuzzy systems and deep learning are very broad in the field of engineering, industrial, business, finance, medicine, and many other areas.

Development and application of fuzzy logic and deep learning through vector machines and neural networks or newly developed algorithms such as deep learning that boosts tree models.

The practical application of fuzzy systems poses additional challenges such as dealing with large, missing, distorted, and uncertain data. Also, interpretability is the most important characteristic that must be achieved using the application of the fuzzy method. Interpretability allows you to understand fuzzy model behavior and it increases confidence in the results.

This special issue focuses on the application of fuzzy models and deep learning in various fields and problems. We expect the papers/report with practical results for various learning methods, discuss the conceptualization of problems, data representation, functional engineering, fuzzy models, critical comparisons with existing technologies, and interpretation.

This special issue entitled, “Analysis, Processing, and Applications of Fuzzy System and Deep Learning”, covers basic, applied, artificial intelligence, control, robotics, data analysis, data mining, decision making, finance and management, information systems, operational research, pattern recognition, and image processing. The anticipated submitted papers are expected to meet the theoretical and practical in application and development using fuzzy system technology and deep learning. The new approaches regarding the fuzzy method and deep learning will be highly wecomed.

Fuzzy method, deep learning, software engineering for fuzzy systems, Fuzzy systems in robotics and mechatronics, data processing, Pattern Recognition's fuzzy system application, Artificial Intelligence.

Published Papers
  • Prediction of Changed Faces with HSCNN
  • Abstract Convolutional Neural Networks (CNN) have been successfully employed in the field of image classification. However, CNN trained using images from several years ago may be unable to identify how such images have changed over time. Cross-age face recognition is, therefore, a substantial challenge. Several efforts have been made to resolve facial changes over time utilizing recurrent neural networks (RNN) with CNN. The structure of RNN contains hidden contextual information in a hidden state to transfer a state in the previous step to the next step. This paper proposes a novel model called Hidden State-CNN (HSCNN). This adds to CNN a… More
  •   Views:734       Downloads:660        Download PDF

  • Image Dehazing Based on Pixel Guided CNN with PAM via Graph Cut
  • Abstract Image dehazing is still an open research topic that has been undergoing a lot of development, especially with the renewed interest in machine learning-based methods. A major challenge of the existing dehazing methods is the estimation of transmittance, which is the key element of haze-affected imaging models. Conventional methods are based on a set of assumptions that reduce the solution search space. However, the multiplication of these assumptions tends to restrict the solutions to particular cases that cannot account for the reality of the observed image. In this paper we reduce the number of simplified hypotheses in order to attain… More
  •   Views:743       Downloads:500       Cited by:7        Download PDF

  • Object Detection for Cargo Unloading System Based on Fuzzy C Means
  • Abstract With the recent increase in the utilization of logistics and courier services, it is time for research on logistics systems fused with the fourth industry sector. Algorithm studies related to object recognition have been actively conducted in convergence with the emerging artificial intelligence field, but so far, algorithms suitable for automatic unloading devices that need to identify a number of unstructured cargoes require further development. In this study, the object recognition algorithm of the automatic loading device for cargo was selected as the subject of the study, and a cargo object recognition algorithm applicable to the automatic loading device is… More
  •   Views:719       Downloads:653       Cited by:1        Download PDF

  • Suggestion of Maintenance Criteria for Electric Railroad Facilities Based on Fuzzy TOPSIS
  • Abstract This paper is on the suggestion of maintenance items for electric railway facility systems. With the recent increase in the use of electric locomotives, the utilization and importance of railroad electrical facility systems are also increasing, but the railroad electrical facility system in Korea is rapidly aging. To solve this problem, various methodologies are applied to ensure operational reliability and stability for railroad electrical facility systems, but there is a lack of detailed evaluation criteria for railroad electrical facility system maintenance. Also, maintenance items must be selected in a scientific and systematic method. Therefore, railroad electrical facility systems are selected… More
  •   Views:703       Downloads:605        Download PDF