Predicting longitudinal dispersion coefficient in natural streams using minimax probability machine regression and multivariate adaptive regression spline
by Sanjiban Sekhar Roy; Pijush Samui
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 19, No. 2, 2021

Abstract: This article employs minimax probability machine regression (MPMR) and multivariate adaptive regression spline (MARS) for prediction of longitudinal dispersion coefficient in natural streams. The variables of hydraulic features such as channel width (B), flow depth (H), flow velocity (U), shear velocity (u*) and geometric features such as channel sinuosity (σ) and channel shape parameter (β) were taken as the input. The dispersion coefficient Kx was the decision parameter for the proposed machine learning models. MARS does not assume any functional relationship between inputs and output. The MARS model is a non-parametric regression model that splits the data and fits each interval into a basis function. MPMR is a probabilistic model which maximises the minimum probability of predicted output. MPMR also provides output within some bound of the true regression function. The proposed study gives an equation for prediction of longitudinal dispersion coefficient based on the developed MARS. The developed MARS has been compared with proposed MPMR. Finally, the performances of the models have been measured by different performance metrics.

Online publication date: Wed, 26-May-2021

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Advanced Intelligence Paradigms (IJAIP):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com