Gaussian process regression to predict incipient motion of alluvial channel

2Citations
Citations of this article
3Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Incipient motion of alluvial channel flow, which relates the beginning of sediment movement, has been extensively studied in the past few decades, and many equations have been developed which essentially differ from each other in derivation and form. As the process is extremely complex, getting deterministic or analytical forms of process phenomena is too difficult. Gaussian process regression (GPR), which is particularly useful in modeling processes about which adequate knowledge of the physics is limited, is presented here as a complementary tool to model the incipient motion problems. The prediction capability of the model has been found to be satisfactory.

Cite

CITATION STYLE

APA

Sehrawat, J., Patel, M., & Kumar, B. (2015). Gaussian process regression to predict incipient motion of alluvial channel. In Advances in Intelligent Systems and Computing (Vol. 336, pp. 431–437). Springer Verlag. https://doi.org/10.1007/978-81-322-2220-0_35

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free