An Example of Artificial Neural Network (ANN) Application for Indirect Estimation of Rock Parameters

被引：216
|
作者：
Yilmaz, I. [1 ]
Yuksek, A. G. [2 ]
机构：
[1] Cumhuriyet Univ, Fac Engn, Dept Geol Engn, Div Appl Geol, TR-58140 Sivas, Turkey
[2] Cumhuriyet Univ, Vocat Sch Sivas, Dept Comp Technol, TR-58140 Sivas, Turkey
来源：
ROCK MECHANICS AND ROCK ENGINEERING | 2008年 / 41卷 / 05期
关键词：
artificial neural network; multiple regression; gypsum; elasticity modulus; unconfined compressive strength;
D O I：
10.1007/s00603-007-0138-7
中图分类号：
P5 [地质学];
学科分类号：
0709 ; 081803 ;
摘要：
A study was conducted to develop an artificial neural network model to determine the modulus of elasticity and unconfined compressive strength of a rock. Multiple regression analysis was used for the study to correlate modulus of elasticity and unconfined compressive strength with the index properties. A feed forward back propagation neural network model was also used for the study to determine the modulus of elasticity and unconfined compressive strength of gypsum. Porosity, slake durability, Schmidt hardness, point load, and strength were also examined during the study. It was also observed that there exist a statistical relationship between elasticity modulus and unconfined compressive strength with slake durability index, point load index, effective porosity, and Schmidt hammer rebound number.
引用
收藏
页码：781 / 795
页数：15
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