Fuzzy model for the prediction of unconfined compressive strength of rock samples

Autor:	M. Alvarez Grima, Robert Babuska
Rok vydání:	1999
Předmět:	Fuzzy clustering Computer simulation Artificial neural network business.industry Concatenation Geotechnical Engineering and Engineering Geology Fuzzy logic Nonlinear system Compressive strength Rock mechanics Artificial intelligence business Algorithm Mathematics
Zdroj:	International Journal of Rock Mechanics and Mining Sciences. 36:339-349
ISSN:	1365-1609
Popis:	A data driven approach to the modeling of unconfined compressive strength of rock samples is presented. Fuzzy logic approach is used to represent a nonlinear relationship as a smooth concatenation of local linear submodels. The partitioning of the input space into fuzzy regions, represented by the individual rules, is obtained through fuzzy clustering. The numerical results are compared with a conventional statistical (multi-linear) model. It is shown that the fuzzy model is not only more accurate but as opposed to other black-box approaches (such as neural networks), it also provides some insight into the nonlinear relationship represented by the model.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::535bd47c0a290480b1dc7416275664b4 https://doi.org/10.1016/s0148-9062(99)00007-8 Zobrazit plný text záznamu Full Text from ScienceDirect