Forecasting River Turbidity using Innovative Machine Learning ...

We aimed to explore the application of ML algorithms to predict turbidity for the Stony Clove watershed in the Ashokan Reservoir catchment and compare the.

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Forecasting River Turbidity Using Innovative Machine Learning Techniques. Turbidity is a vital metric of water quality that has adverse effects on aquatic life.

Prediction of water turbidity in a marine environment using machine ...

Artificial neural network (ANN), Support vector regression (SVR) and Long short term memory-recurrent neural network (LSTM-RNN) algorithms are used to ...

Integrating remote sensing and machine learning to detect turbidity ...

This work aims to integrate Machine Learning methods specialized in anomaly detection with data obtained from remote sensing images to identify with high ...

(PDF) Machine Learning for Water Quality Index Forecasting

model demonstrates strong predictive potential and can be considered an effective tool for WQI forecasting in various scenarios,. supported by ...

Prediction of the Area of High-Turbidity Water in the Yatsushiro Sea ...

Based on this background, we propose a machine learning method to predict the area of high-turbidity water around an estuary on the following ...

Turbidity assessment in coastal regions combining machine ...

Developed a framework combining machine learning, numerical modeling, and remote sensing for accurate turbidity prediction. • Need for uniform ...

Application of artificial intelligence for forecasting surface quality ...

This study used machine learning and deep learning algorithms to calculate the WQI with minimal input data (water quality parameters) to reduce the cost of ...

Turbidity Prediction in a River Basin by Using Artificial Neural ...

Bearing this in mind, turbidity values have been predicted here by using artificial neural networks (ANNs) from the remaining measured water ...

Machine Learning for Water Quality Index Forecasting

This study aims to forecast water quality in the Tumkur district, Karnataka state, India, to increase pollution levels.

Enhancing Turbidity Modeling in the Mississippi River Using ...

Online Sequential. Extreme Learning Machine in River Water Quality (Turbidity) Prediction: A Comparative Study on. Different Data Mining ...

Water quality prediction using machine learning models based on ...

[9] predicted the Yangtze River Basin's drinking water quality utilising a long short-term memory (LSTM) network. Dissolved oxygen (DO), pH, ...

Machine Learning Based Long‐Term Water Quality in the Turbid ...

However, robust algorithms are required to retrieve TSS and Chl-a from MODIS/Aqua images in the turbid Pearl River Estuary (PRE). Here, a new ...

"Advancing Deep Learning Techniques For Turbidity Forecasting In ...

By building and analyzing these forecast models, this research aims to improve the accuracy and reliability of turbidity forecasts, optimizing river and ...

Developing an ensembled machine learning model for predicting ...

In this research, the numerical method is first used to calculate the WQI and identify the classes for validating the prediction results. Then, ...

Application of machine learning in river water quality management

Among the most commonly used WQ parameters for surface, WQ prediction are DO, WT, pH, SS, nitrates (NOx), TDS, EC, turbidity, BOD, and COD.

Prediction of the Turbidity Distribution Characteristics in a Semi ...

The findings demonstrate a promising alignment between the machine learning model's predictions and the theoretically assumed sediment behavior, highlighting ...

Evaluation of water quality based on artificial intelligence

In order to ascertain the most accurate prediction model for water quality, five machine learning (ML) algorithms were employed: support vector ...

Session HS3.1 - Meeting Organizer

Topics addressed in the session include: * Predictive and exploratory models based on the methods of statistics, computational intelligence, machine learning ...

Using IoT and Machine Learning to help protect Kenya's Rivers

We are also developing machine learning methods to deal with anomalous sensor measurements and make predictions. In future we plan to ...