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

Submission Deadline: 30 July 2022
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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.

Summary

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.


Keywords
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
  • 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:86       Downloads:64        Download PDF

  • Efficient Autonomous Defense System Using Machine Learning on Edge Device
  • Abstract As a large amount of data needs to be processed and speed needs to be improved, edge computing with ultra-low latency and ultra-connectivity is emerging as a new paradigm. These changes can lead to new cyber risks, and should therefore be considered for a security threat model. To this end, we constructed an edge system to study security in two directions, hardware and software. First, on the hardware side, we want to autonomically defend against hardware attacks such as side channel attacks by configuring field programmable gate array (FPGA) which is suitable for edge computing and identifying communication status to… More
  •   Views:218       Downloads:199        Download PDF