✦ LIBER ✦

Prediction of sand ripple geometry under waves using an artificial neural network

✍ Scribed by Bing Yan; Qing-He Zhang; Onyx W.H. Wai

Book ID: 113511245
Publisher: Elsevier Science
Year: 2008
Tongue: English
Weight: 1024 KB
Volume: 34
Category: Article
ISSN: 0098-3004
DOI: 10.1016/j.cageo.2008.03.002

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Prediction of extrusion pressure using a

Prediction of extrusion pressure using an artificial neural network

✍ Y.Y Li; J Bridgwater 📂 Article 📅 2000 🏛 Elsevier Science 🌐 English ⚖ 789 KB

Prediction of pelvic organ prolapse usin

Prediction of pelvic organ prolapse using an artificial neural network

✍ Christopher J. Robinson; Steven Swift; Donna D. Johnson; Jonas S. Almeida 📂 Article 📅 2008 🏛 Elsevier Science 🌐 English ⚖ 662 KB

Prediction of air pollutants by using an

Prediction of air pollutants by using an artificial neural network

✍ Sang Hyun Sohn; Sea Cheon Oh; Yeong-Koo Yeo 📂 Article 📅 1999 🏛 Springer US 🌐 English ⚖ 957 KB

Prediction of breast cancer malignancy u

Prediction of breast cancer malignancy using an artificial neural network

✍ Carey E. Floyd Jr.; Joseph Y. Lo; A. Joon Yun; Daniel C. Sullivan; Phyllis J. Ko 📂 Article 📅 1994 🏛 John Wiley and Sons 🌐 English ⚖ 475 KB 👁 2 views

Prediction of surface roughness profiles

Prediction of surface roughness profiles for milled surfaces using an artificial neural network and fractal geometry approach

✍ I.A. El-Sonbaty; U.A. Khashaba; A.I. Selmy; A.I. Ali 📂 Article 📅 2008 🏛 Elsevier Science 🌐 English ⚖ 355 KB

Artificial neural networks (ANNs) models were developed for the analysis and prediction of the relationship between the cutting conditions and the corresponding fractal parameters of machined surfaces in face milling operation. These models can help manufacturers to determine the appropriate cutting

Prediction of cold rolling texture of st

Prediction of cold rolling texture of steels using an Artificial Neural Network

✍ Abhijit Brahme; Myrjam Winning; Dierk Raabe 📂 Article 📅 2009 🏛 Elsevier Science 🌐 English ⚖ 357 KB