Abstract
Paper presents method of construction neural model of the sea bottom. Constructed model consisted of set of smaller models (local approximators). For model approximation was used set of RBF networks with various kernels, what enabled approximation of the entire model by networks with different structure. Experimental results show that in this way we can obtain better results than applying neural model based on local approximators with the same structure.
Cite
CITATION STYLE
Lubczonek, J. (2004). Hybrid neural model of the sea bottom surface. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3070, pp. 1154–1160). Springer Verlag. https://doi.org/10.1007/978-3-540-24844-6_181
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