Abstract
Population based methods, and among them, the population learning algorithm (PLA), can be used to train artificial neural networks. The paper studies the probability distribution of solution time to a sub-optimal target in the example implementation of the PLA-trained artificial neural network. The distribution is estimated by means of the computational experiment. Graphical analysis technique is used to compare the theoretical and empirical distributions and estimate parameters of the distributions. It has been observed that the solution time to a sub-optimal target value fits a two parameter exponential distribution.
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Czarnowski, I., Jȩdrzejowicz, P. (2004). Probability Distribution of Solution Time in ANN Training Using Population Learning Algorithm. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds) Artificial Intelligence and Soft Computing - ICAISC 2004. ICAISC 2004. Lecture Notes in Computer Science(), vol 3070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24844-6_21
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DOI: https://doi.org/10.1007/978-3-540-24844-6_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22123-4
Online ISBN: 978-3-540-24844-6
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