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Universal approximation with uninorm-based fuzzy neural networks
2011
2011 Annual Meeting of the North American Fuzzy Information Processing Society
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Fuzzy neural networks are hybrid models capable to approximate functions with high precision and to generate transparent models, enabling the extraction of valuable information from the resulting topology ...
In this paper we will show that the recently proposed fuzzy neural network based on weighted uninorms aggregations uniformly approximates any real functions on any compact set. ...
INTRODUCTION Fuzzy neural networks are a synergy between fuzzy set theory, as a mechanism for information compactation and knowledge representation, and neural networks. ...
doi:10.1109/nafips.2011.5752000
fatcat:co3rlqwq2nbg3hpryoav76fznq
Backpropagation method with type-2 fuzzy weight adjustment for neural network learning
2012
2012 Annual Meeting of the North American Fuzzy Information Processing Society (NAFIPS)
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In this paper a neural network learning method with type-2 fuzzy weight adjustment is proposed. ...
In this work an ensemble neural network of three neural networks and average integration for obtain the final result is present. The proposed approach is applied to a case of time series prediction. ...
In Fig. 4 an example of neural network architecture with type 2 fuzzy weights is shown: Figure 4 . Example of neural network architecture with type 2 fuzzy weights. ...
doi:10.1109/nafips.2012.6291056
fatcat:bvkqq6rm2zbe7egofivdqsjka4
IReNNS: A recurrent neural network with independent neurons and its application in bioinformatics
2009
NAFIPS 2009 - 2009 Annual Meeting of the North American Fuzzy Information Processing Society
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We propose a simplified architecture for a recurrent neural network designed for learning from structures. We describe the architecture and the implementation and show the performances of the net. ...
The 28th North American Fuzzy Information Processing Society Annual Conference (NAFIPS2009) Cincinnati, Ohio, USA -June 14 -17, 2009 VII. ...
A standard feed-forward neural network, for example, can process data which can be represented in fixeddimension vectors. ...
doi:10.1109/nafips.2009.5156388
fatcat:x3bfurfflngg7l5wfbspwbjmq4
Development and Research of Intelligent PID Controller Based on Fuzzy Neural Network
2014
Open Automation and Control Systems Journal
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In this paper, intelligent fuzzy control theory is introduced in the model of neural network algorithm, and the neural network system is improved by the PID controller, which has realized the feedback ...
In order to verify the validity and reliability of the designed intelligent control PID algorithm based on the fuzzy neural network in this paper, the algorithm is carried on the programming by using Matlab ...
In the process of information transfer, network is always in the state with constantly changing and adjustment. ...
doi:10.2174/1874444301406011474
fatcat:3kdhy5tv5reo5gjdefo72dr4pi
Research and Application of Key Technique of Artificial Intelligence to Process Information
2016
International Journal of Hybrid Information Technology
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This thesis, research the key artificial intelligence technology to process information, including the artificial neural network, fuzzy theory and others. ...
and processing of information. ...
Hence, the functions of the neural networks could be continuously improved via the automatic adjustment to the system parameters in accordance with the features and property of the information to be processed ...
doi:10.14257/ijhit.2016.9.12.23
fatcat:uwwpcx625zaxbclwnsf6og37ni
The Algorithm of CFNN Image Data Fusion in Multi-sensor Data Fusion
2014
Sensors & Transducers
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CFNN hybrid system in Multi-sensor data fusion introduced fuzzy logic reasoning and neural network adaptive, self-learning ability, and using fuzzy neurons, so networking skills appropriate to adjust the ...
input and output fuzzy membership function, and can dynamically optimize fuzzy reasoning in global by means of compensated logic algorithm, to make the network more fault tolerance, stability and speed ...
Finally, the compensation fuzzy neural network parallel architecture and parallel processing mechanism makes information processing speed is very fast, able to meet the requirements of real-time processing ...
doaj:7f88e4ec98f54455bf149bc5ca8fc29f
fatcat:z75mf44icrfebjxpokxqm2tsvi
An Image Compression Scheme Based on Fuzzy Neural Network
2015
TELKOMNIKA (Telecommunication Computing Electronics and Control)
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processing in the nodes; thus greatly improving the transparency of fuzzy neural network. ...
Fuzzy neural network effectively integrates neural network technology and fuzzy technology; combines learning, selfadaptivity, imagination and identity and uses rule-based reasoning and fuzzy information ...
Fuzzy neural network mechanism Fuzzy neural network is the process to handle samples fuzzily, and the samples should be constantly transformed into regular forms in the handling process. ...
doi:10.12928/telkomnika.v13i1.1270
fatcat:e2kjsafqyvas3hddjkbjrkap2m
Tools of the Neuro-Fuzzy Model of Information Risk Management in National Security
2019
International Journal of Engineering and Advanced Technology
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The neuro-fuzzy model considered in the article is based on the advantages of fuzzy logic and artificial neural networks. ...
It eliminates the disadvantages of the fuzzy logical model and takes full advantage of neural networks. ...
Neural network structure In order to illustrate the process of processing information by a neural network, we take a section of the network consisting of two input neurons and one hidden neuron. ...
doi:10.35940/ijeat.f8842.088619
fatcat:czbqh33sefcbllmclzd5olirla
A Method of Information Fusion Based on Fuzzy Neural Network and Its Application
2017
ITM Web of Conferences
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Therefore, this paper combines neural network with fuzzy logic [6, 7] , and puts forward a fault diagnosis method by using fuzzy neural network, which is more close to the human thinking [8] [9] [10] . ...
In the field of fault diagnosis, this method can deal with uncertain and imprecise information by using fuzzy theory, and has a high self-study capability based on neural network. ...
processing the pure processing value data to can process the fuzzy information data. ...
doi:10.1051/itmconf/20171101015
fatcat:z6rsrkqss5el5bohiq5calzi2u
Application of the Fuzzy Neural Network Algorithm in the Exploration of the Agricultural Products E-Commerce Path
2020
Intelligent Automation and Soft Computing
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The Fuzzy Neural Network Algorithm Fuzzy neural networks are compared to traditional neural networks, and the fuzzy neural network has two more processes than traditional neural networks. ...
The fuzzy process of the fuzzy neural network algorithm was a great improvement and optimization of the traditional neural network algorithm. ...
doi:10.32604/iasc.2020.013935
fatcat:qhov4b7b3vcnxccgq7uxpg3jgm
ANALYSIS OF CLASSICAL MODELS OF CLASSIFICATION OF SLOWLY FORMED PROCESSES
2022
Zenodo
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In this regard, the researches of a number of scientists on fuzzy sets, neural networks, fuzzy logical conclusions and evolutionary algorithms were analyzed. ...
The theory of fuzzy sets, the use of fuzzy relations in the modeling of objects and the information about the object in the linguistic form are presented again. ...
Different methods are used to study neural networks, i.e. neural networks with fuzzy signals and/or fuzzy weights. neural network + fuzzy logic (neuro-fuzzy); fuzzy logic + genetic algorithm; fuzzy ...
doi:10.5281/zenodo.7156184
fatcat:cryrl7hbrjcitjiij6x2crh7vq
Image Edge Detection Algorithm Based on Fuzzy Radial Basis Neural Network
2021
Advances in Mathematical Physics
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of fuzzy radial basis fusion discrimination, in terms of preprocessing algorithm, comparing the denoising effect of mean and median filters with different template sizes on paper images with added noise ...
The image edge detection algorithm based on fuzzy radial basis fuser can not only speed up the image preprocessing, meet the real-time detection, and reduce the amount of data processed by the upper computer ...
A fuzzy radial basis neural network is a kind of feedforward neural network with a large amount of information processing and strong fault tolerance, which has the advantages of strong approximation ability ...
doi:10.1155/2021/4405657
fatcat:bo2pa5govvhfvle2qagasly2ke
Research on Fuzzy Control Method in EDM Machine
2014
International Journal of Hybrid Information Technology
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Based on the analysis of the characteristics of the edm process as the foundation, proposed a fuzzy control technology. In edm process, using fuzzy neural network control technology. ...
According to the characteristics of the fuzzy controller, combined with the advantages of artificial neural network, to correct the adverse effect of some imperfect rules, improve the fast response ability ...
The combination of fuzzy system and artificial neural network is con stituted fuzzy neural control system, this is the one with adaptive system of human sensory and cognitive components, the neural network ...
doi:10.14257/ijhit.2014.7.3.10
fatcat:dg3m34bisffepobz56g3zvlf74
A Fuzzy Neural Network Fault Diagnostic System
2014
International Journal of Computer Applications
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Recently, it is found that, neural networks and fuzzy logic control have widely used for the diagnostic devices. Fuzzy logic systems provide high processing speed but lower computing power. ...
Therefore, the proposed system introduces the fuzzy neural network fault diagnostic system for diagnosis the complex devices. ...
It can combine the advantages of fuzzy fault diagnosis with those of the neural network. ...
doi:10.5120/16305-5531
fatcat:ipem5f5mv5hfdkmdktwg66e6um
Study of Intelligent Diagnosis System for Mechanism Wear Fault Based on Fuzzy-Neural Networks
[chapter]
2011
IFIP Advances in Information and Communication Technology
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Mechanism wear faults can be diagnosed to apply the fuzzy-neural network and fault causes are determined. ...
This paper analysises how to create the characteristic vector of wear particles and standard wear particles spectrum by combine the characteristics of mechanism wear fault,and the fuzzy-neural network ...
Fuzzy-neural network is combined with fuzzy theory and neural networks . ...
doi:10.1007/978-3-642-18369-0_36
fatcat:6bbocdjjjnftvoh5wgnse3fs4m
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