Add to ORKGThis report presents two further experiments over the aphid data set. The first is an evaluation of the adaptive abilities of backpropagation of errors trained MLP and a comparison of these capabilities with the Simple Evolving Connectionist System (SECoS). The goal of the first experiment is to compare both the performance and the adaptive abilities of the two models. The second experiment is an investigation of the sensitivity of the SECoS to the exclusion of various input variables. The goal of the second experiment is to determine which of the thirteen input variables contributes the most to the modelling of the problem, that is, which variable the network is most sensitive to
Artificial Neural Networks (ANN) of Multilayer Perceptron (MLP) type are widely known and used in a...
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer S...
This document is the initial report on a systematic approach to the application of MLP to the aphid ...
This report presents two further experiments over the aphid data set. The first is an evaluation of ...
Most application work within neural computing continues to employ multi-layer perceptrons (MLP). Tho...
A adaptive back-propagation algorithm for multilayered feedforward perceptrons was discussed. It was...
A multilayer perceptron is a feed forward artificial neural network model that maps sets of input da...
Multilayer perceptrons (MLPs) (1) are the most common artificial neural networks employed in a large...
The perceptron is essentially an adaptive linear combiner with the output quantized to ...
International audienceNeural networks are used increasingly as statistical models. The performance o...
this report also have been published on ESANN '93 [Schiffmann et al., 1993]. The dataset used i...
I'' Abstract 'U The multi-layer perceptron is a type of feed forward neural network f...
This paper investigates the effectiveness and efficiency of two competitive (predator-prey) evolutio...
Backpropagation of errors (BP) trained Multi-Layer Perceptrons (MLP) (Rumelhart et al., 1986) have p...
Here the authors examine the nature of the mnemonic structures that underlie the ability of animals ...
Artificial Neural Networks (ANN) of Multilayer Perceptron (MLP) type are widely known and used in a...
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer S...
This document is the initial report on a systematic approach to the application of MLP to the aphid ...
This report presents two further experiments over the aphid data set. The first is an evaluation of ...
Most application work within neural computing continues to employ multi-layer perceptrons (MLP). Tho...
A adaptive back-propagation algorithm for multilayered feedforward perceptrons was discussed. It was...
A multilayer perceptron is a feed forward artificial neural network model that maps sets of input da...
Multilayer perceptrons (MLPs) (1) are the most common artificial neural networks employed in a large...
The perceptron is essentially an adaptive linear combiner with the output quantized to ...
International audienceNeural networks are used increasingly as statistical models. The performance o...
this report also have been published on ESANN '93 [Schiffmann et al., 1993]. The dataset used i...
I'' Abstract 'U The multi-layer perceptron is a type of feed forward neural network f...
This paper investigates the effectiveness and efficiency of two competitive (predator-prey) evolutio...
Backpropagation of errors (BP) trained Multi-Layer Perceptrons (MLP) (Rumelhart et al., 1986) have p...
Here the authors examine the nature of the mnemonic structures that underlie the ability of animals ...
Artificial Neural Networks (ANN) of Multilayer Perceptron (MLP) type are widely known and used in a...
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer S...
This document is the initial report on a systematic approach to the application of MLP to the aphid ...