Deep neuro-fuzzy systems (DNFSs) have been successfully applied to real-world problems using the efficient learning process of deep neural networks (DNNs) and reasoning aptitude from fuzzy inference systems (FIS). This study provides a comprehensive review of DNFS dividing it into two essential ...
Fuzzy systems (FSs) are popular and interpretable machine learning methods, represented by the adaptive neuro-fuzzy inference system (ANFIS). However, they have difficulty dealing with high-dimensional data due to the curse of dimensionality. To effectively handle high-dimensional data and ensure optim...
Deep fuzzy systems (DFSs) are models built on top of DL structures with fuzzy logic systems (FLSs). DFS aims to overcome the lack of interpretability of DL systems and the limitations of FLS when dealing with high-dimensional data. DFS is often referred to in the literature as an explainabl...
2021, Future Generation Computer Systems Citation Excerpt : Some solutions have been developed to address this challenge [39,40]. Velliangiri and Pandey [41] proposed an approach that combines fuzzy and taylor-elephant herd optimization (FT-EHO) inspired by the Deep Belief Network (DBN) for dete...
classify schizophrenic patients and healthy controls. The results show that the fuzzy entropy (FuzzyEn) feature is more significant than the fast Fourier transform (FFT) feature in brain topography. The deep learning (DL) method that we propose achieves an average accuracy of 99.22% with FuzzyEn...
D Wang,M Alhamdoosh - 《Neurocomputing》 被引量: 131发表: 2013年 Boosting Simplified Fuzzy Neural Networks Fuzzy neural networks are a powerful machine learning technique, that can be used in a large number of applications. Proper learning of fuzzy neural networ... A Natekin,A Knoll - Inte...
A Neuro-fuzzy Network with Reinforcement Learning Algorithms for Swarm Learning An internal model of autonomous mobile robots (agent) is proposed in this paper. A TSK-type fuzzy net is used as a classifier of environment information, i... T Kuremoto,Y Yamano,LB Feng,... - 《Lecture Notes...
In addition, the heart rate variability (HRV) derived from an ECG is regulated by the central nervous and autonomic systems, and closely related to the DoA during surgery [18,19,20]. Therefore, HRV may be used as an important supplementary method of EEG monitoring in terms of DoA ...
Medical image classification plays an essential role in clinical treatment and teaching tasks. However, the traditional method has reached its ceiling on performance. Moreover, by using them, much time and effort need to be spent on extracting and select
15 proposed a neuro-fuzzy classifier for the detection of cardiomegaly in digital chest radiography. The work used classical morphology operations to segment the lungs for a neuro-fuzzy classifier and thus obtained the feature values to measure heart enlargement. Sema Candemir et al.16 reported a...