Special Issues

Fuzzy Soft Computing for Real-time Complex Applications

Submission Deadline: 25 June 2022 (closed) View: 35

Guest Editors

Dr. Chi Lin, Dalian University of Technology, China.
Dr. Chang Wu Yu, Chung Hua University, Taiwan.
Dr. Ning Wang, Rowan University, USA.

Summary

Real-time complex applications are prevalent and an integral part of our lives today. The performance requirements of these applications often introduce many challenges that necessitate the application of new techniques to develop these systems. Real-time complex applications require several algorithms, techniques, and methods that consider different sources of uncertainty in time, data, and application. The solution is fuzzy soft computing. Soft computing generally offers flexibility and robustness in complex real-time applications, while fuzzy soft computing can provide simple, easy-to-understand, and extendable models. Fuzzy soft computing is a methodology aimed to build intelligent systems using the power of fuzziness, neural networks, and fuzzy logic. Fuzzy soft computing for complex real-time applications can be an effective approach for dealing with uncertainty and imprecision in data, redundant information, and inconsistent information. These techniques are particularly effective in complex real-time applications because they are interested in optimal solutions to problems that are either too complicated or too difficult for the traditional computing approaches to produce efficient results.

 

Performance and reliability in complex applications such as self-driving vehicles medical and factory automation can depend on the ability to process real-time data. This data may be conflicting, vague, or uncertain, so new techniques are needed to provide accurate solutions Since real-time applications are often characterized by continuous data streams, varying and unpredictable workloads, temporal reliability constraints, complex interdependencies or relationships, and online processing with stringent response time requirements. These demands often challenge the capabilities of conventional computing methodologies such as simulation. The value of fuzzy soft computing is that it offers a methodology for tackling such applications which use linguistic representations but provide existing methods with improved interpretability, better robustness to noisy data, and more interactions with human users. However, the real-time application of fuzzy soft computing has been a challenging research field, owing to the inherent use of imprecise knowledge in “fuzzy” linguistic variables. The distinctive feature of fuzzy techniques is their ability to integrate and correlate data from diverse sources; as a result, many models in the area of fuzzy soft computing have exhibited higher accuracy and better performance than traditional models. The application of soft computing algorithms and technologies to solve complex problems is explored in this special issue.

 

This special issue brings together recent state-of-the-art research on fuzzy soft computing for complex real-time applications. The goal is to present recent advances in the field of fuzzy soft computing and its applications, including multi-objective optimization, multimedia communication and networking, IoT, autonomous systems, smart city, cybersecurity, and cyber-physical systems, biomedical image processing and healthcare, as well as intelligent control systems for autonomous vehicles.

 

Advances in fuzzy soft computing for high dimensional data analytics in complex real-time applications

Fuzzy soft computing applications for intelligent systems and automation

Fuzzy soft computing assisted new innovative tools and techniques for real-time complex applications

Advanced aspects of fuzzy soft computing for efficient management of complex real-time applications

Trends in fuzzy decision making and soft computing for real-time cyber physical systems

Fuzzy soft computing for pattern recognition in real-time complex applications

Trends in neuro fuzzy computing for real-time complex applications data classification and processing

Role of metaheuristic algorithms and approaches in real-time complex applications

Multi-objective optimization of real-time complex applications with fuzzy soft computing approaches

Fuzzy soft computing for real-time image optimization in real-time complex applications

Evolutionary computation in complex real-time systems


Keywords

soft computing
intelligent systems and automation
Evolutionary computation
neuro fuzzy
cyber-physical systems

Published Papers


  • Open Access

    ARTICLE

    Enhanced Perturb and Observe Control Algorithm for a Standalone Domestic Renewable Energy System

    N. Kanagaraj, Obaid Aldosari, M. Ramasamy, M. Vijayakumar
    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2291-2306, 2023, DOI:10.32604/iasc.2023.039101
    (This article belongs to the Special Issue: Fuzzy Soft Computing for Real-time Complex Applications)
    Abstract The generation of electricity, considering environmental and economic factors is one of the most important challenges of recent years. In this article, a thermoelectric generator (TEG) is proposed to use the thermal energy of an electric water heater (EWH) to generate electricity independently. To improve the energy conversion efficiency of the TEG, a fuzzy logic controller (FLC)-based perturb & observe (P&O) type maximum power point tracking (MPPT) control algorithm is used in this study. An EWH is one of the major electricity consuming household appliances which causes a higher electricity price for consumers. Also, a… More >

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