✦ LIBER ✦

Estimation of strength parameters of rock using artificial neural networks

✍ Scribed by Kripamoy Sarkar; Avyaktanand Tiwary; T. N. Singh

Publisher: Springer
Year: 2010
Tongue: English
Weight: 566 KB
Volume: 69
Category: Article
ISSN: 1435-9529
DOI: 10.1007/s10064-010-0301-3

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Estimating Rock Cuttability using Regres

Estimating Rock Cuttability using Regression Trees and Artificial Neural Networks

✍ Bulent Tiryaki 📂 Article 📅 2008 🏛 Springer 🌐 English ⚖ 167 KB

An Example of Artificial Neural Network

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

✍ I. Yılmaz; A. G. Yuksek 📂 Article 📅 2007 🏛 Springer 🌐 English ⚖ 254 KB

Estimation of soil compaction parameters

Estimation of soil compaction parameters by using statistical analyses and artificial neural networks

✍ O. Günaydın 📂 Article 📅 2008 🏛 Springer ⚖ 620 KB

Estimation of effective stress parameter

Estimation of effective stress parameter of unsaturated soils by using artificial neural networks

✍ C. Kayadelen 📂 Article 📅 2008 🏛 John Wiley and Sons 🌐 English ⚖ 276 KB

## Abstract Great efforts are required for determination of the effective stress parameter χ, applying the unsaturated testing procedure, since unsaturated soils that have the three‐phase system exhibit complex mechanical behavior. Therefore, it seems more reasonable to use the empirical methods fo

Prediction of strength properties of som

Prediction of strength properties of some schistose rocks from petrographic properties using artificial neural networks

✍ Singh, V.K ;Singh, D ;Singh, T.N 📂 Article 📅 2001 🏛 Elsevier Science 🌐 English ⚖ 333 KB

A Computational Estimation of Cyclic Mat

A Computational Estimation of Cyclic Material Properties Using Artificial Neural Networks

✍ A. Tomasella; C. el Dsoki; H. Hanselka; H. Kaufmann 📂 Article 📅 2011 🏛 Elsevier 🌐 English ⚖ 941 KB

The structural durability design of components requires the knowledge of cyclic material properties. These parameters are strongly dependent on environmental conditions and manufacturing processes, and require many experimental tests to be correctly determined. Considering time and costs, it is not