Architecture of Evolving Fuzzy Neural Network (adapted
Evolving Fuzzy Neural Network for Phishing s Detection
... emails, Evolving Fuzzy Neural Network (EFuNN), filters email sequentially INTRODUCTION Such a type of threats, phishing e-mails, is used to steal sensitive and personal data or user's' account ...
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Evolving Fuzzy Min-max Neural Network for Outlier Detection
... a fuzzy concept and required in many real time operations, we believe that the hybridization of fuzzy logic and neural network for outlier detection is a promising area of ...
9
The development of a weighted evolving fuzzy neural network for PCB sales forecasting
... 2005 Elsevier Ltd. All rights reserved. Keywords: Sales forecasting; Weighted evolving fuzzy neural network; Grey relation analysis; Printed circuit board sales 1. Introduction Printed circuit ...
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An Efficient Method for Selecting the Optimal Structure of a Fuzzy Neural Network Architecture
... artificial neural networks with soft com- puting enables to construct learning machines that are superior compared to classical artificial neural networks, because knowledge can be extracted and explained ...
10
Evolving spiking neural network - a survey
... the evolving spiking neural network architecture ...the evolving nature of the network, it is possible to accumulate knowledge as it becomes available, without the requirement of ...
12
Fuzzy Neural Network for Clustering and Classification
... a fuzzy neural network for clustering and ...this fuzzy neural network two training algorithm are implemented for clustering and ...General Fuzzy min max Neural ...
7
Evolving a Deep Neural Network Training Time Estimator
... In [ 14 ], the predictor is trained from existing architectures (restricted to Fully Connected Networks -FCN- and CNN) and their respective data sets. The model estimates the runtime per type of layer, under different ...
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Integrated feature and parameter optimization for an evolving spiking neural network
... b) Chromosome used in vQEA for simultaneously optimizing feature and parameter space. The optimization task consists in a proper identification of an optimal feature subset, which maximizes the classification accuracy ...
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Title: Evolving Neural Network for Kernel Principal Component Analysis
... of evolving connectionist systems [20], which implies not only the tunning of synaptic weights of the neural network, but also its architecture directly in the learning ...[7] evolving ...
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Hybrid Neural Network Architecture for On Line Learning
... Keywords: Neural Networks, Instantaneously Trained Networks, Back-Propagation, On-Line Learning ...conventional neural networks are not con- venient to use because of their slow ...
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Improving decision tree and neural network learning for evolving data-streams
... Despite the regression version of the ESHT achieving good results, the classification version did not performed as expected. On classification prob- lems, we showed that our proposed architecture is able to ...
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Phishing Dynamic Evolving Neural Fuzzy Framework for Online Detection Zero-day Phishing
... connectionist architecture try to make easy of evolving processes with knowledge ...be neural network or set of networks, work continuously in time and adapt their structure and functionality ...
5
Diagnosing angina using a simple neural network architecture
... a fuzzy inference engine may be able to solve this problem, but it is probably just easier to use a more sop- histicated multi-layer neural network ...
5
Evolving the Global Network Architecture
... Standards Real time data Reporting Availability Management Global Global Global Incident Management Global Global Global Change Management Global Local Local Capacity Management G[r] ...
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Correntropy Based Evolving Fuzzy Neural System
... Badong Chen (M’10, SM’13) received the B.S. and M.S. degrees in control theory and engineering from Chongqing University, Chongqing, China, in 1997 and 2003, respectively, and the Ph.D. degree in computer science and ...
14
Fuzzy Signature Neural Network
... l Data-driven way to create fuzzy signatures l Self-determined fuzzy signatures number l Improve HE’s fuzzy signature neural. network[r] ...
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Evolving Neural Network CMAC and its Applications
... a network CMAC a number of difficulties in the selection of parameters such as the number of levels and the quantization levels, the shape of the receptive field, the type of applied information hashing algorithm ...
8
Evaluation of fuzzy regression models by fuzzy neural network
... Feedforward neural network Learning algorithm a b s t r a c t In this paper, a novel hybrid method based on fuzzy neural network for approximate fuzzy coefficients (parameters) ...
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Neural Network Regressions with Fuzzy Clustering
... Neural Network Regressions with Fuzzy Clustering ...hybrid neural network regression models with unsupervised fuzzy clustering is proposed for clustering nonparametric regression ...
6
A VLSI architecture for neural network chips
... The above examples demonstrate that analogue circuits are suitable for implementing small-scale, specialised neural network applications that can be integrated into one single chip86,135. This comes as an ...
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