✦ LIBER ✦

Estimation of formation strength index of aquifer from neural networks

✍ Scribed by Bieng-Zih Hsieh; Chih-Wen Wang; Zsay-Shing Lin

Book ID: 113511306
Publisher: Elsevier Science
Year: 2009
Tongue: English
Weight: 468 KB
Volume: 35
Category: Article
ISSN: 0098-3004
DOI: 10.1016/j.cageo.2008.11.010

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Application of neural networks for estim

Application of neural networks for estimation of concrete strength

✍ Jong In Kim; Doo Kie Kim 📂 Article 📅 2002 🏛 Korean Society of Civil Engineers 🌐 English ⚖ 914 KB

Estimation of heterogeneous aquifer para

Estimation of heterogeneous aquifer parameters from piezometric data using ridge functions and neural networks

✍ A. Mantoglou 📂 Article 📅 2003 🏛 Springer 🌐 English ⚖ 697 KB

Estimation of strength parameters of roc

Estimation of strength parameters of rock using artificial neural networks

✍ Kripamoy Sarkar; Avyaktanand Tiwary; T. N. Singh 📂 Article 📅 2010 🏛 Springer 🌐 English ⚖ 566 KB

Mechanical strength and setting times es

Mechanical strength and setting times estimation of hydroxyapatite cement by using neural network

✍ H. Baseri; S.M. Rabiee; F. Moztarzadeh; M. Solati-Hashjin 📂 Article 📅 2010 🏛 Elsevier Science ⚖ 803 KB

Neural network prediction of the AE inde

Neural network prediction of the AE index from the PC index

✍ J. Takalo; J. Timonen 📂 Article 📅 1999 🏛 Elsevier Science 🌐 English ⚖ 446 KB

Simulation of spring flows from a karst

Simulation of spring flows from a karst aquifer with an artificial neural network

✍ Caihong Hu; Yonghong Hao; Tian-Chyi J. Yeh; Bo Pang; Zening Wu 📂 Article 📅 2008 🏛 John Wiley and Sons 🌐 English ⚖ 377 KB

## Abstract In China, 9·5% of the landmass is karst terrain and of that 47,000 km^2^ is located in semiarid regions. In these regions the karst aquifers feed many large karst springs within basins of thousands of square kilometres. Spring discharges reflect the fluctuation of ground water level and