Comparison of the performance of decision tree (DT) algorithms and extreme learning machine (ELM) model in the prediction of water quality of the Upper Green River watershed-Reference-Cited by-同舟云学术

Comparison of the performance of decision tree (DT) algorithms and extreme learning machine (ELM) model in the prediction of water quality of the Upper Green River watershed

Published:2021-10-04 Issue:11 Volume:93 Page:2360-2373
ISSN:1061-4303
Container-title:Water Environment Research
language:en
Short-container-title:Water Environment Research

Author:

Anmala Jagadeesh¹^ORCID,Turuganti Venkateswarlu¹

Affiliation:

1. Department of Civil Engineering Birla Institute of Technology and Science, Pilani, Hyderabad Campus Hyderabad Telangana India

Funder

Council of Scientific and Industrial Research, India

Publisher

Wiley

Subject

Water Science and Technology,Ecological Modelling,Waste Management and Disposal,Pollution,Environmental Chemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/wer.1642

Reference67 articles.

1. GIS and Artificial Neural Network–Based Water Quality Model for a Stream Network in the Upper Green River Basin, Kentucky, USA

2. Statistical assessment and neural network modeling of stream water quality observations of Green River watershed, KY, USA

3. River water quality index prediction and uncertainty analysis: A comparative study of machine learning models

4. Neuronal Brownian dynamics for salinity of river basins’ water management

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