Effects of the 2018 and 2019 floods in Kerala, India on the existing multivariate statistical models Online publication date: Fri, 31-May-2024
by P.G. Dileep Kumar; Narayanan Viswanath; Sobha Cyrus; Benny Mathews Abraham
International Journal of Hydrology Science and Technology (IJHST), Vol. 17, No. 4, 2024
Abstract: The state of Kerala, India, experienced severe flood events during August 2018 and 2019. The aim of this paper was to study the post-flood relevance of the multiple linear regression (MLR) and adaptive neuro-fuzzy inference system (ANFIS) models formed before floods, for Kozhikode city, Kerala, India. For this, water samples were collected from 49 different locations in the above city, in September 2019. Both the existing MLR and ANFIS models were found to be less effective on post-flood data. Hence, new MLR, structural equation (SE) and ANFIS models were formed separately for severely and less severely flood-affected samples by performing bootstrapping to address the problems caused by the small datasets. The root mean square error (RMSE) and Lorenz curve were used to analyse the performance of the models. It was observed that ANFIS models performed better than MLR models.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
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 Hydrology Science and Technology (IJHST):
Login with your Inderscience username and 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
Our Blog 
Follow us on Twitter 
Visit us on Facebook