ArticleEnvironmental science and pollution research international2020
A water quality prediction method based on the multi-time scale bidirectional long short-term memory network.
Article in Environmental science and pollution research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 90 citations in OpenAlex.
- Towards Synoptic Water Monitoring Systems: A Review of AI Methods for Automating Water Body Detection and Water Quality Monitoring Using Remote Sensing.Sensors (Basel, Switzerland) · 2022Pooled it
- A novel soft sensor framework based on adaptive LSTM ensemble for robust water quality prediction in wastewater treatment plants.Water science and technology : a journal of the International Association on Water Pollution Research · 2026Article
- Water Quality Prediction Based on Multi-Task Learning.International journal of environmental research and public health · 2022Article
- An improved adaptive neuro fuzzy inference system model using conjoined metaheuristic algorithms for electrical conductivity prediction.Scientific reports · 2022Article
- Water quality prediction in sea cucumber farming based on a GRU neural network optimized by an improved whale optimization algorithm.PeerJ. Computer science · 2022Article
- A study on water quality prediction by a hybrid CNN-LSTM model with attention mechanism.Environmental science and pollution research international · 2021Article
- Review
- A Fishery Water Quality Monitoring and Prediction Evaluation System for Floating UAV Based on Time Series.Sensors (Basel, Switzerland) · 2021Article
- Monitoring and prediction of dust concentration in an open-pit mine using a deep-learning algorithm.Journal of environmental health science & engineering · 2021Article
- Multivariate Streamflow Simulation Using Hybrid Deep Learning Models.Computational intelligence and neuroscience · 2021Article
- Application of soft computing to predict water quality in wetland.Environmental science and pollution research international · 2021Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As an important factor affecting the mangrove wetland ecosystem, water quality has become the focus of attention in recent years. Therefore, many studies have focused on the prediction of water quality to help establish a regulatory framework for the assessment and management of water pollution and ecosystem health. To make a more accurate and comprehensive forecast analysis of water quality, we propose a method for water quality prediction based on the multi-time scale bidirectional LSTM network. In the method, we improve data integrity and data volume through data preprocessing. And the network processes input data forward and backward and considers the dependencies at multiple time scales. Besides, we use the Box-Behnken experimental design method to adjust hyper-parameters in the process of modeling. In this study, we apply this method to the water quality prediction research of Beilun Estuary, and the performance of our proposed model is evaluated and compared with other models. The experiment results show that this model has better performance in water quality prediction than that of using LSTM or bidirectional LSTM alone. Graphical Abstract Schematic of research work.
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