Prediction of Water Quality Using SoftMax-ELM Optimized Using Adaptive Crow-Search Algorithm-Reference-Cited by-同舟云学术

Prediction of Water Quality Using SoftMax-ELM Optimized Using Adaptive Crow-Search Algorithm

Published:2023 Issue: Volume:11 Page:140900-140913
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Chakravarthy S. R. Sannasi¹^ORCID,Bharanidharan N.²^ORCID,Venkatesan Vinoth Kumar²,Abbas Mohamed³,Rajaguru Harikumar¹^ORCID,Mahesh T. R.⁴^ORCID,Venkatesan Krishnamoorthy⁵^ORCID

Affiliation:

1. Department of ECE, Bannari Amman Institute of Technology, Sathyamangalam, India

2. School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore, India

3. Electrical Engineering Department, College of Engineering, King Khalid University, Abha, Saudi Arabia

4. Department of Computer Science and Engineering, JAIN (Deemed-to-be University), Bengaluru, India

5. Department of Mathematics, Units of Basic Sciences, Arba Minch University, Sawla Campus, Arba Minch, Ethiopia

Funder

Deanship of Scientific Research at King Khalid University (KKU) through the Research Group Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10343161.pdf?arnumber=10343161

Reference44 articles.

1. Indices and models of surface water quality assessment: Review and perspectives

2. A systematic review on machine learning algorithms used for forecasting lake‐water level fluctuations

3. Water quality prospective in Twenty First Century: Status of water quality in major river basins, contemporary strategies and impediments: A review

4. Drinking water quality and the SDGs

5. Water Quality Classification by Integration of Attribute-Realization and Support Vector Machine for the Chao Phraya River

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