In this paper a comparison between a dynamic NARX-type neural network model and a support vector machine (SVM) model with external recurrences for estimating ...
The results show the advantages of SVM modeling, especially concerning Model Predictive Output estimations of the state variable (MSE < 1.0), ...
Comparison of Neural Networks and Support Vector. Machine Dynamic Models for State Estimation in. Semiautogenous Mills. Gonzalo Acuña1 and Millaray Curilem2. 1 ...
In this paper a comparison between a dynamic NARX-type neural network model and a support vector machine (SVM) model with external recurrences for estimating ...
Comparison of Neural Networks and Support Vector Machine Dynamic Models for State Estimation in Semiautogenous Mills. https://doi.org/10.1007/978-3-642-05258 ...
Bibliographic details on Comparison of Neural Networks and Support Vector Machine Dynamic Models for State Estimation in Semiautogenous Mills.
In this paper a comparison between a dynamic NARX-type neural network model and a support vector machine (SVM) model with external recurrences for estimating ...
13 References ; Comparison of Neural Networks and Support Vector Machine Dynamic Models for State Estimation in Semiautogenous Mills · G. AcuñaMillaray Curilem.
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The results are compared to those of a simple neural network acting as an estimator. They show the advantages of the Neural-MHSE, especially concerning ...
The comparison results demonstrate that the recurrent neural network is the most accurate prediction model, followed by genetic programming and support vector ...