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42 443 (0,254s)

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RBF Neural Network Properties Assessment for Combustion Engine Compression Pressures Estimation

Example of combustion engine absolute compression pressure values estimation by use of RBF neural network shows basic properties of standard RBF neural network and generalized regression neura...

JT - Pohon, motory a paliva

  • 2005
  • D
Result

Hybrid RBF + GA Neural Network for Electricity Load Forecast

The paper evaluate RBF neural network as a method of artificial intelligence that Hybrid RBF + GA neural network outperform RBF neural network and number of baselines. W...

IN - Informatika

  • 2012
  • D
Result

RBF NEURAL NETWORK APPLICATIONS USING JNNS SIMULATOR

The paper deals about using artificial neural network and the architecture RBF for time series data. The process of set up architecture is explai, the first part describes RBF function. . In the second part is expl...

IN - Informatika

  • 2012
  • D
  • Link
Result

RBF Neural Network Implementation of Fuzzy Systems: Application to Time Series Modeling

powerful fuzzy modeling technique. Neural networks and fuzzy logic models are based on very similar underlying mathematics. The similarity between RBF networks and fuzzy modelsis noted in detail. Then, we propose ...

AH - Ekonomie

  • 2007
  • D
Result

Sales time series modeling using Box-Jenkins methodology and rbf neural networks

We examine the class of RBF neural network models for the approximation models RBF networks and fuzzy models is noted. Time series approximation by applying RBF neural networks o...

AH - Ekonomie

  • 2009
  • D
Result

RBF Neural Networks for Time Series Modelling and Forecasting

In this paper the classic and soft radial basis function (RBF) neural networks are modified by Gaussian cloud concept. We concern with learning aspects of granular RBF networks. We also compare the results...

IN - Informatika

  • 2015
  • D
Result

RBF neural network implementation of fuzzy systems: Application to time series modeling

powerful fuzzy modeling technique. Neural networks and fuzzy logic models are based on very similar underlying mathematics. The similarity between RBF networks and fuzzy modelsis noted in detail. Then, we propose ...

IN - Informatika

  • 2007
  • D
Result

Fuzzy Logic and Granular RBF Neural Networks: An Application to the Input-Output Function Estimation of Sales Processes

In this paper the outputs of RBF neurons of an RBF neural network are normalized and theRBF function is modified by Gaussian cloud concept. These RBF neural networks, i. e. soft or granul...

AH - Ekonomie

  • 2008
  • D
Result

Approximation and Forecasting Ability of Various RBF and Granular NNW: Application to Sales Process Modelling

powerful fuzzy modeling technique. Neural networks and fuzzy logic models are based on very similar underlying mathematics. The similarity between RBF networks and fuzzy modelsis noted in detail. Then, we propose ...

AH - Ekonomie

  • 2009
  • D
Result

RBF Neural Networks and Radial Fuzzy Systems

RBF neural networks are an efficient tool for acquisition and representation of the parameters of the network. Contrary to neural networks, fuzzy systems allow a more neural network

IN - Informatika

  • 2015
  • D
  • Link
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