Development of fuzzy-GMDH model optimized by GSA to predict rock tensile strength based on experimental datasets

The tensile strength (TS) of the rock is one the most key parameters in designing process of foundations and tunnels structures. However, direct techniques for TS determination (laboratory investigations) are not efficient with respect to cost and time. This investigation attempts to develop an inno...

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Veröffentlicht in:	Neural computing & applications 2020-09, Vol.32 (17), p.14047-14067
Hauptverfasser:	Harandizadeh, Hooman, Armaghani, Danial Jahed, Mohamad, Edy Tonnizam
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial Intelligence Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Correlation coefficients Data Mining and Knowledge Discovery Datasets Dry density Fuzzy sets Group method of data handling Hybrid systems Image Processing and Computer Vision Laboratories Load tests Optimization Original Article Prediction models Predictions Probability and Statistics in Computer Science Process parameters Search algorithms Sensitivity analysis Statistical methods Tensile strength
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