Research and Applications of Neural Networks and Fuzzy Logic

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D2: Operations Research and Fuzzy Decision Making".

Deadline for manuscript submissions: 30 November 2025 | Viewed by 885

Special Issue Editor


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Guest Editor
Department of Computer Science, Tijuana Institute of Technology/TECNM, Tijuana, Mexico
Interests: deep neural networks; fuzzy logic; machine learning; artificial intelligence; artificial neural networks; convolutional neural networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to invite submissions to a Special Issue of Mathematics (MDPI) under the titled "Research and Applications of Neural Networks and Fuzzy Logic".

This Special Issue aims to explore the latest innovations and research combining neural networks and fuzzy logic, focusing on their practical applications in fields such as pattern recognition, control systems, decision-making, artificial intelligence, data analysis, and health care or medical applications. Additionally, this Special Issue aims to explore advancements in convolutional neural networks (CNNs), deep learning techniques, the development of optimal neural network architectures, and the critical need for explainable artificial intelligence (XAI). This Special Issue seeks to highlight innovative research, practical implementations, and theoretical advancements that enhance the understanding and application of neural networks and fuzzy logic in complex real-world challenges.

Contributions may address, but are not limited to, the following topics:

  • Neural networks and fuzzy logic for pattern recognition and image analysis.
  • Advanced control systems integrating fuzzy logic and neural networks.
  • Decision-making processes using fuzzy logic and neural networks.
  • Artificial intelligence and machine learning models integrating fuzzy logic for greater accuracy and flexibility.
  • Data analysis and optimization using hybrid neuro-fuzzy systems.
  • Health care and medical applications involving neuro-fuzzy systems and AI for diagnostics, treatment planning, and predictive analysis.
  • Applications of CNNs and deep learning in combination with fuzzy logic.
  • Optimization of neural network architectures for better performance and efficiency.
  • Development of explainable AI (XAI) systems using fuzzy logic for interpretability and transparency.

Prof. Dr. Claudia I. González
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • neural networks
  • fuzzy logic
  • neuro-fuzzy systems
  • explainable AI
  • optimal neural network architectures
  • artificial intelligence

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Published Papers (1 paper)

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Research

18 pages, 12097 KiB  
Article
Adaptive Outdoor Cleaning Robot with Real-Time Terrain Perception and Fuzzy Control
by Raul Fernando Garcia Azcarate, Akhil Jayadeep, Aung Kyaw Zin, James Wei Shung Lee, M. A. Viraj J. Muthugala and Mohan Rajesh Elara
Mathematics 2025, 13(14), 2245; https://doi.org/10.3390/math13142245 - 10 Jul 2025
Viewed by 337
Abstract
Outdoor cleaning robots must operate reliably across diverse and unstructured surfaces, yet many existing systems lack the adaptability to handle terrain variability. This paper proposes a terrain-aware cleaning framework that dynamically adjusts robot behavior based on real-time surface classification and slope estimation. A [...] Read more.
Outdoor cleaning robots must operate reliably across diverse and unstructured surfaces, yet many existing systems lack the adaptability to handle terrain variability. This paper proposes a terrain-aware cleaning framework that dynamically adjusts robot behavior based on real-time surface classification and slope estimation. A 128-channel LiDAR sensor captures signal intensity images, which are processed by a ResNet-18 convolutional neural network to classify floor types as wood, smooth, or rough. Simultaneously, pitch angles from an onboard IMU detect terrain inclination. These inputs are transformed into fuzzy sets and evaluated using a Mamdani-type fuzzy inference system. The controller adjusts brush height, brush speed, and robot velocity through 81 rules derived from 48 structured cleaning experiments across varying terrain and slopes. Validation was conducted in low-light (night-time) conditions, leveraging LiDAR’s lighting-invariant capabilities. Field trials confirm that the robot responds effectively to environmental conditions, such as reducing speed on slopes or increasing brush pressure on rough surfaces. The integration of deep learning and fuzzy control enables safe, energy-efficient, and adaptive cleaning in complex outdoor environments. This work demonstrates the feasibility and real-world applicability for combining perception and inference-based control in terrain-adaptive robotic systems. Full article
(This article belongs to the Special Issue Research and Applications of Neural Networks and Fuzzy Logic)
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