Title: RESEARCH COMMUNICATIONS OF THE 28th ECVIM-CA CONGRESS Document date: 2018_12_19
ID: r79h9yzz_913
Snippet: Neural based methods in biosciences proved to be a powerful tool in transforming intelligently available information into valuable knowledge, such as models. This study considered two types of ANNs: Multiâ€Layer Perceptron (MLP) and Radial Basis Function (RBF), known as universal approximators for bounded continuous functions. The training data for both networks was built by adding recordings with low intercorrelation and relevant for the entire.....
Document: Neural based methods in biosciences proved to be a powerful tool in transforming intelligently available information into valuable knowledge, such as models. This study considered two types of ANNs: Multiâ€Layer Perceptron (MLP) and Radial Basis Function (RBF), known as universal approximators for bounded continuous functions. The training data for both networks was built by adding recordings with low intercorrelation and relevant for the entire dataset. The input neural vector was formed considering adjustable lags in data samples to capture the dynamic behavior of the modeled process. Each neural network was designed with single hidden layer and a number of neurons inducted by experimental tuning.
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