HDTO-DeepAR: A novel hybrid approach to forecast surface water quality indicators-Reference-Cited by-同舟云学术

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HDTO-DeepAR: A novel hybrid approach to forecast surface water quality indicators

Published:2024-02 Issue: Volume:352 Page:120091
ISSN:0301-4797
Container-title:Journal of Environmental Management
language:en
Short-container-title:Journal of Environmental Management

Author:

Singh Rosysmita Bikram^ORCID,Patra Kanhu Charan^ORCID,Pradhan Biswajeet^ORCID,Samantra Avinash^ORCID

Publisher

Elsevier BV

Reference90 articles.

1. Water quality indices based on bioassessment: The biotic indices;Abbasi;J. Water Health,2011

2. Deep learning with dipper throated optimization algorithm for energy consumption forecasting in smart households;Abdelhamid;Energies,2022

3. Innovative feature selection method based on hybrid Sine cosine and dipper throated optimization algorithms;Abdelhamid;IEEE Access,2023

4. Statistical and trend analysis of water quality and quantity data for the Strymon River in Greece;Antonopoulos;Hydrol. Earth Syst. Sci.,2001

5. Probabilistic wind power forecasting using optimized deep auto-regressive recurrent neural networks;Arora;IEEE Trans. Ind. Inform.,2022

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3. Slope deformation prediction based on noise reduction and deep learning: a point prediction and probability analysis method;Frontiers in Earth Science;2024-05-27

4. Surface water quality index forecasting using multivariate complementing approach reinforced with locally weighted linear regression model;Environmental Science and Pollution Research;2024-04-23

5. Integrated PCA–RNN approach for surface water quality assessment in the Mahanadi river system;International Journal of Environmental Science and Technology;2024-02-27

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