Surface water quality index forecasting using multivariate complementing approach reinforced with locally weighted linear regression model-Reference-Cited by-同舟云学术

Surface water quality index forecasting using multivariate complementing approach reinforced with locally weighted linear regression model

Published:2024-04-23 Issue:22 Volume:31 Page:32382-32406
ISSN:1614-7499
Container-title:Environmental Science and Pollution Research
language:en
Short-container-title:Environ Sci Pollut Res

Author:

Hai Tao,Ahmadianfar Iman,Halder Bijay,Heddam Salim,Al-Areeq Ahmed M.,Demir Vahdettin,Kilinc Huseyin Cagan,Abba Sani I.,Tan Mou Leong,Homod Raad Z.,Yaseen Zaher Mundher^ORCID

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11356-024-33027-0.pdf

Reference55 articles.

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2. Ahmadianfar I, Heidari AA, Gandomi AH et al (2021a) RUN beyond the metaphor: an efficient optimization algorithm based on Runge Kutta method. Expert Syst Appl 181:115079

3. Ahmadianfar I, Heidari AA, Noshadian S et al (2022a) INFO: an efficient optimization algorithm based on weighted mean of vectors. Expert Syst Appl 195:116516. https://doi.org/10.1016/j.eswa.2022.116516

4. Ahmadianfar I, Jamei M, Chu X (2020b) A novel hybrid wavelet-locally weighted linear regression (W-LWLR) model for electrical conductivity (EC) prediction in surface water. J Contam Hydrol. https://doi.org/10.1016/j.jconhyd.2020.103641

5. Ahmadianfar I, Khajeh Z, Asghari-Pari S-A, Chu X (2019) Developing optimal policies for reservoir systems using a multi-strategy optimization algorithm. Appl Soft Comput 80:888–903. https://doi.org/10.1016/j.asoc.2019.04.004

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