ArticleHeliyon2022
Long Short-Term Memory-based simulation study of river happiness evaluation - A case study of Jiangsu section of Huaihe River Basin in China.
Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
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Corrections and comments
- Retraction · 2025-03-18Author Unresponsive · Computer-Aided Content or Computer-Generated Content · Investigation by Journal/Publisher · Unreliable Results and/or Conclusions · Upgrade/Update of Prior Notice(s) ·
- Erratum issued
- Retracted
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Real-time prediction of the state of the river itself and the degree of its benefit to the people is the leading way to achieve human-water harmony. Using the indicator scoring method as the evaluation method, we used the river evaluation data and results with time series characteristics as features and labels and applied the concept of transfer learning to Long Short-Term Memory to establish six subsystems, including water safety, water quality, economic contribution, water ecology, water management and water culture, to conduct a real-time rolling evaluation simulation study on the degree of river happiness in the Jiangsu section of the Huaihe River Basin in China. The empirical results show that the maximum Root Mean Square Error (RMSE) of the training set and test set of each system is 0.0226, and the lowest coefficient of determination R
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