Utilizing Machine Learning Algorithms to Predict Accuracy of the Index of Relative Tectonic Activity (IRTA), Dhansiri (North) River Basin in India and Bhutan-Reference-Cited by-同舟云学术

Utilizing Machine Learning Algorithms to Predict Accuracy of the Index of Relative Tectonic Activity (IRTA), Dhansiri (North) River Basin in India and Bhutan

Published:2024 Issue: Volume:12 Page:60482-60495
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Roy Shayani¹^ORCID,Mandal Pritam²^ORCID,Chowdhury Amitava³,Abdullah-Al-Wadud M.⁴^ORCID,Seikh Ariyan H.⁵,Seikh Ayan H.⁵,Ghosh Manojit²^ORCID,Mukhopadhyay Ananya¹^ORCID

Affiliation:

1. Department of Earth Sciences, Indian Institute of Engineering Science and Technology (IIEST), Howrah, Shibpur, India

2. Department of Metallurgy and Materials Engineering, Indian Institute of Engineering Science and Technology (IIEST), Howrah, Shibpur, India

3. Department of Computer Science and Engineering, Pandit Deendayal Energy University, Gandhinagar, India

4. Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

5. Department of Computer Science and Engineering, Motilal Nehru National Institute of Technology Allahabad at Prayagraj, Prayagraj, India

Funder

King Saudi University, Riyadh, Saudi Arabia, through the Researchers Supporting Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10508800.pdf?arnumber=10508800

Reference52 articles.

1. Response of alluvial rivers to slow active tectonic movement

2. Encyclopedia of Geomorphology

3. Geomorphometry and landform mapping: What is a landform?

4. Drainage-basin characteristics

5. EROSIONAL DEVELOPMENT OF STREAMS AND THEIR DRAINAGE BASINS; HYDROPHYSICAL APPROACH TO QUANTITATIVE MORPHOLOGY