Performance Evaluation of Deep Learning Models for Water Quality Index Prediction: A Comparative Study of LSTM, TCN, ANN, and MLP
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Abstract (arXiv)
Environmental monitoring and predictive modeling of the Water Quality Index (WQI) through the assessment of the water quality.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 8 of its 38 references that are in the map. First posted on arXiv 3 Nov 2024.
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8 of 38 references.
References · 8
- 2016Temporal Convolutional Networks for Action Segmentation and Detectioncited by 508
- 2021Well-tuned Simple Nets Excel on Tabular Datasetscited by 151
- 2017Weakly Supervised Action Localization by Sparse Temporal Pooling Networkcited by 100
- 2016Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representationscited by 55
- 2021Learnable Dynamic Temporal Pooling for Time Series Classificationcited by 13
- 2022Parallel Spatio-Temporal Attention-Based TCN for Multivariate Time Series Predictioncited by 12
- 2019Quantifying Long Range Dependence in Language and User Behavior to improve RNNscited by 5
- 2018Deep Adaptive Temporal Pooling for Activity Recognitioncited by 3
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