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A robust and explainable deep learning model based on an LSTM-CNN framework for reliable FDOM prediction in water quality monitoring: Incorporating SHAP analysis for enhanced interpretability
Research article (Process Safety and Environmental Protection, 2025) · cited 12× · AI/ML
A robust and explainable deep learning model based on an LSTM-CNN framework for reliable FDOM prediction in water quality monitoring: Incorporating SHAP analysis for enhanced interpretability
Summary
A robust and explainable deep learning model based on an LSTM-CNN framework for reliable FDOM prediction in water quality monitoring: Incorporating SHAP analysis for enhanced interpretability is a scholarly article[1].
Key Facts
A robust and explainable deep learning model based on an LSTM-CNN framework for reliable FDOM prediction in water quality monitoring: Incorporating SHAP analysis for enhanced interpretability's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). A robust and explainable deep learning model based on an LSTM-CNN framework for reliable FDOM prediction in water quality monitoring: Incorporating SHAP analysis for enhanced interpretability. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-robust-and-explainable-deep-learning-model-based-on-an-lstm-cnn-framework-for-reliable-fdom-prediction-in-water-qualit
MLA“A robust and explainable deep learning model based on an LSTM-CNN framework for reliable FDOM prediction in water quality monitoring: Incorporating SHAP analysis for enhanced interpretability.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-robust-and-explainable-deep-learning-model-based-on-an-lstm-cnn-framework-for-reliable-fdom-prediction-in-water-qualit.
BibTeX@misc{4ortxyz_a-robust-and-explainable-deep-learning-model-based-on-an-lstm-cnn-framework-for-reliable-fdom-prediction-in-water-qualit_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A robust and explainable deep learning model based on an LSTM-CNN framework for reliable FDOM prediction in water quality monitoring: Incorporating SHAP analysis for enhanced interpretability}}, year = {2026}, url = {https://4ort.xyz/entity/a-robust-and-explainable-deep-learning-model-based-on-an-lstm-cnn-framework-for-reliable-fdom-prediction-in-water-qualit}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A robust and explainable deep learning model based on an LSTM-CNN framework for reliable FDOM prediction in water quality monitoring: Incorporating SHAP analysis for enhanced interpretability — https://4ort.xyz/entity/a-robust-and-explainable-deep-learning-model-based-on-an-lstm-cnn-framework-for-reliable-fdom-prediction-in-water-qualit (retrieved 2026-05-24)
