AIMC Topic: Rivers

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Machine learning approaches for adequate prediction of flow resistance in alluvial channels with bedforms.

Water science and technology : a journal of the International Association on Water Pollution Research Jan 1, 2024
In natural rivers, flow conditions are mainly dependent on flow resistance and type of roughness. The interactions among flow and bedforms are complex in nature as bedform dynamics primarily regulate the flow resistance. Manning's equation is the mos...
Rivers Water Movements Models, Theoretical Machine Learning
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Assessing the impacts of climate change on streamflow dynamics: A machine learning perspective.

Water science and technology : a journal of the International Association on Water Pollution Research Nov 1, 2023
This study investigates changes in river flow patterns, in the Hunza Basin, Pakistan, attributed to climate change. Given the anticipated rise in extreme weather events, accurate streamflow predictions are increasingly vital. We assess three machine ...
Climate Change Machine Learning Water Resources Neural Networks, Computer Rivers
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A novel approach to precipitation prediction using a coupled CEEMDAN-GRU-Transformer model with permutation entropy algorithm.

Water science and technology : a journal of the International Association on Water Pollution Research Aug 1, 2023
The accurate forecasting of precipitation in the upper reaches of the Yellow River is imperative for enhancing water resources in both the local and broader Yellow River basin in the present and future. While many models exist for predicting precipit...
Water Resources Entropy Algorithms Rivers Neural Networks, Computer
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Streams, rivers and data lakes: an introduction to understanding modern electronic healthcare records.

Clinical medicine (London, England) Jul 1, 2023
As foundation doctors, we have often found ourselves informing patients that a certain aspect of their medical information cannot be immediately found, either because it is on an electronic system we cannot access, or it is in a hospital that is unli...
Artificial Intelligence Delivery of Health Care Humans Hospitals Rivers Electronic Health Records Physicians
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Application of wavelet theory to enhance the performance of machine learning techniques in estimating water quality parameters (case study: Gao-Ping River).

Water science and technology : a journal of the International Association on Water Pollution Research Mar 1, 2023
There are several methods for modeling water quality parameters, with data-based methods being the focus of research in recent decades. The current study aims to simulate water quality parameters using modern artificial intelligence techniques, to en...
Fuzzy Logic Rivers Water Quality Machine Learning Environmental Monitoring Artificial Intelligence
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Comparing machine-learning-based black box techniques and white box models to predict rainfall-runoff in a northern area of Iraq, the Little Khabur River.

Water science and technology : a journal of the International Association on Water Pollution Research Feb 1, 2023
The rainfall-runoff process is one of the most complex hydrological phenomena. Estimating runoff in the basin is one of the main conditions for planning and optimal use of rainfall. Using machine learning models in various sciences to investigate phe...
Computer Simulation Rivers Machine Learning Iraq
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Hybrid wavelet-gene expression programming and wavelet-support vector machine models for rainfall-runoff modeling.

Water science and technology : a journal of the International Association on Water Pollution Research Dec 1, 2022
It is critical to use research methods to collect and regulate surface water to provide water while avoiding damage. Following accurate runoff prediction, principled planning for optimal runoff is implemented. In recent years, there has been an incre...
Computer Simulation Support Vector Machine Water Rivers Gene Expression Water Movements
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Estimating the incubated river water quality indicator based on machine learning and deep learning paradigms: BOD5 Prediction.

Mathematical biosciences and engineering : MBE Sep 1, 2022
As an indicator measured by incubating organic material from water samples in rivers, the most typical characteristic of water quality items is biochemical oxygen demand (BOD) concentration, which is a stream pollutant with an extreme circumstance of...
Deep Learning Environmental Monitoring Machine Learning Neural Networks, Computer Water Quality Quality Indicators, Health Care Rivers
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Dissolved oxygen modelling of the Yamuna River using different ANFIS models.

Water science and technology : a journal of the International Association on Water Pollution Research Nov 1, 2021
Dissolved oxygen (DO) is one of the prime parameters for assessing the water quality of any stream. Thus, the accurate estimation of DO is necessary to evolve measures for maintaining the riverine ecosystem and designing appropriate water quality imp...
Water Quality Fuzzy Logic Rivers Ecosystem Oxygen
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Granular computing-neural network model for prediction of longitudinal dispersion coefficients in rivers.

Water science and technology : a journal of the International Association on Water Pollution Research Nov 1, 2019
Successful application of one-dimensional advection-dispersion models in rivers depends on the accuracy of the longitudinal dispersion coefficient (LDC). In this regards, this study aims to introduce an appropriate approach to estimate LDC in natural ...
Rivers Artificial Intelligence Neural Networks, Computer Fuzzy Logic
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