Predictive Analytics For Groundwater Resources Using SVM And Deep Radial Basis Approaches In Smart City Planning For Feature Extraction And Prediction-Reference-Cited by-同舟云学术

Predictive Analytics For Groundwater Resources Using SVM And Deep Radial Basis Approaches In Smart City Planning For Feature Extraction And Prediction

Published:2024-03-15 Issue: Volume:336 Page:1292-1297
ISSN:
Container-title:2024 2nd International Conference on Disruptive Technologies (ICDT)
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Author:

N Padmavathi¹,Rafee Shaik Mohammad²,Ahmed Salman³,Kanagavalli N.⁴,Gangwar Prashant Kumar⁵,Meenakshi S.⁶

Affiliation:

1. RMD Engineering College,Department of Electronics and Instrumentation Engineering,Chennai,Tamilnadu,India

2. Sasi Institute of Technology & Engineering,Department of AI&ML,Tadepalligudem,Andhra Pradesh,India

3. Aligarh Muslim University,Interdisciplinary Department of Remote Sensing & GIS Applications,Aligarh,Uttar Pradesh,India

4. Rajalakshmi Institute of Technology,Department of Computer Science and Engineering,Chennai,Tamilnadu,India

5. Woldia University,Department of Construction Technology & Management,Woldia Town,Ethiopia

6. R.M.K. Engineering College,Department of Science and Humanities (General Engineering),Kavarapettai,Tamilnadu,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10488912/10488915/10488966.pdf?arnumber=10488966

Reference15 articles.

1. Application of machine learning in groundwater quality modeling - A comprehensive review

2. Application of Machine Learning in Water Resources Management: A Systematic Literature Review

3. Smart Water Resource Management Using Artificial Intelligence—A Review

4. Intelligent Automated Interference for the Protection of Road Safety

5. Sediment load prediction in Johor river: deep learning versus machine learning models