Neural Networks and Fuzzy Systems: A Synergistic Approach
Abstract
This study explores the foundational principles and components of neural networks and fuzzy systems, emphasizing their unique properties and collaborative potential. The integration of these techniques, known as neuro-fuzzy systems, has demonstrated remarkable effectiveness in addressing complex, real-world problems. This paper highlights the essential characteristics of neural networks and fuzzy systems, delves into their hybridization, and examines the neuro-fuzzy process and its various frameworks. The aim is to provide a comprehensive understanding of these synergistic approaches and their transformative impact on problem-solving across diverse domains.
Full Text:
PDFReferences
Fausett, L.V. (1994). Fundamentals of neural networks: architectures, algorithms, and applications.
Wu, S., & Er, M.J. (2000). Dynamic fuzzy neural networks-a novel approach to function approximation. IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society, 30 2, 358-64 .
Lin, C., & Lu, Y. (1996). A neural fuzzy system with fuzzy supervised learning. IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society, 26 5, 744-63 .
Rahul Reddy Nadikattu. 2016 THE EMERGING ROLE OF ARTIFICIAL INTELLIGENCE IN MODERN SOCIETY. International Journal of Creative Research Thoughts. 4, 4 ,906-911.
Leng, G., Prasad, G., & Mcginnity, T.M. (2004). An on-line algorithm for creating self-organizing fuzzy neural networks. Neural networks : the official journal of the International Neural Network Society, 17 10, 1477-93 .
Saneifard, R. (2011). Some properties of neural networks in designing fuzzy systems. Neural Computing and Applications, 21, 215-220.
Liu, F. (2010). Design for self-organizing fuzzy neural networks based on adaptive evolutionary programming. 2010 2nd International Conference on Advanced Computer Control, 3, 251-254.
Leng, G., Mcginnity, T.M., & Prasad, G. (2006). Design for Self-Organizing Fuzzy Neural Networks Based on Genetic Algorithms. IEEE Transactions on Fuzzy Systems, 14, 755-766.
Qiao, J., & Wang, H. (2008). A self-organizing fuzzy neural network and its applications to function approximation and forecast modeling. Neurocomputing, 71, 564-569.
Liu, F., & Er, M.J. (2012). A Novel Efficient Learning Algorithm for Self-Generating Fuzzy Neural Network with Applications. International journal of neural systems, 22 1, 21-35 .
Xiao-hui, Z., & Yi-bing, S. (2014). Optimization and Implementation of Self-Organization Fuzzy Neutral Network Control Algorithm. The Open Automation and Control Systems Journal, 6.
Refbacks
- There are currently no refbacks.