Machine Learning versus Mathematical Model to Estimate the Transverse Shear Stress Distribution in a Rectangular Channel

no code implementations • 6 Mar 2021 • Babak Lashkar-Ara, Niloofar Kalantari, Zohreh Sheikh Khozani, Amir Mosavi

The results of the sensitivity analysis show that the most influential parameter for the SSD in a smooth rectangular channel is the dimensionless parameter B/H, Where the transverse coordinate is B, and the flow depth is H. With the parameters (b/B), (B/H) for the bed and (z/H), (B/H) for the wall as inputs, the modeling of the GP was better than the other one.

BIG-bench Machine Learning

Shear Stress Distribution Prediction in Symmetric Compound Channels Using Data Mining and Machine Learning Models

no code implementations • 20 Dec 2019 • Zohreh Sheikh Khozani, Khabat Khosravi, Mohammadamin Torabi, Amir Mosavi, Bahram Rezaei, Timon Rabczuk

Finally, the most powerful data mining method which studied in this research (RF) compared with two well-known analytical models of Shiono and Knight Method (SKM) and Shannon method to acquire the proposed model functioning in predicting the shear stress distribution.

BIG-bench Machine Learning