AIMC Topic: Rivers

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SCA-Former: transformer-like network based on stream-cross attention for medical image segmentation.

Physics in medicine and biology Dec 8, 2023
. Deep convolutional neural networks (CNNs) have been widely applied in medical image analysis and achieved satisfactory performances. While most CNN-based methods exhibit strong feature representation capabilities, they face challenges in encoding l...
Image Processing, Computer-Assisted Rivers Neural Networks, Computer
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Deep learning-based total suspended solids concentration classification of stream water surface images captured by mobile phone.

Environmental monitoring and assessment Nov 20, 2023
The continuous monitoring of total suspended solids (TSS) in streams plays an important role in the management of hydrological processes, and TSS is also a decisive parameter in the control of pollution in streams. Determination of TSS involves both ...
Water Environmental Monitoring Deep Learning Rivers Neural Networks, Computer
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An integrated modelling framework for multiple pollution source identification in surface water.

Journal of environmental management Sep 29, 2023
Pollution source identification is vital in water safety management. An integrated simulation-optimization modelling framework comprising a process-based hydrodynamic water quality model, artificial neural network surrogate model and particle swarm o...
Water Quality Rivers Computer Simulation Algorithms Neural Networks, Computer
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Use of machine learning and deep learning to predict particulate Cs concentrations in a nuclearized river.

Journal of environmental radioactivity Sep 15, 2023
Cesium-137, discharged by nuclear installations under normal operations and deposited in watersheds following atmospheric testing and accidents (i.e. Chernobyl, Fukushima …), has been studied for decades. Thus, modelling of Cs concentration in rivers...
Water Dust Deep Learning Machine Learning Cesium Radioisotopes Fukushima Nuclear Accident Rivers Water Pollutants, Radioactive Radiation Monitoring Japan
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Application of empirical mode decomposition, particle swarm optimization, and support vector machine methods to predict stream flows.

Environmental monitoring and assessment Aug 29, 2023
Modeling stream flows is vital for water resource planning and flood and drought management. In this study, the performance of hybrid models constructed by combining least square support vector machines (LSSVM), empirical model decomposition (EMD), a...
Environmental Monitoring Rivers Support Vector Machine Desert Climate Droughts
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Convolutional neural network-multi-kernel radial basis function neural network-salp swarm algorithm: a new machine learning model for predicting effluent quality parameters.

Environmental science and pollution research international Aug 23, 2023
A wastewater treatment plant (WWTP) is an essential part of the urban water cycle, which reduces concentration of pollutants in the river. For monitoring and control of WWTPs, researchers develop different models and systems. This study introduces a ...
Rivers Algorithms Neural Networks, Computer Biological Oxygen Demand Analysis Machine Learning
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Modeling the effect of meteorological variables on streamflow estimation: application of data mining techniques in mixed rainfall-snowmelt regime Munzur River, Türkiye.

Environmental science and pollution research international Aug 12, 2023
Revealing the dynamic link between rainfall and runoff, which are the main components of the hydrological cycle, is significant for the planning and managing water resources, disaster risk management, and construction of water structures. This study ...
Floods Fuzzy Logic Rivers Neural Networks, Computer Algorithms
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Long-lead streamflow forecasting using computational intelligence methods while considering uncertainty issue.

Environmental science and pollution research international Jun 27, 2023
While some robust artificial intelligence (AI) techniques such as Gene-Expression Programming (GEP), Model Tree (MT), and Multivariate Adaptive Regression Spline (MARS) have been frequently employed in the field of water resources, documents aimed to...
Artificial Intelligence Water Resources Uncertainty Trees Rivers Lead Forecasting
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Two-Stream Network One-Class Classification Model for Defect Inspections.

Sensors (Basel, Switzerland) Jun 20, 2023
Defect inspection is important to ensure consistent quality and efficiency in industrial manufacturing. Recently, machine vision systems integrating artificial intelligence (AI)-based inspection algorithms have exhibited promising performance in vari...
Rivers Algorithms Artificial Intelligence
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Damage Detection and Localization of Bridge Deck Pavement Based on Deep Learning.

Sensors (Basel, Switzerland) May 28, 2023
Bridge deck pavement damage has a significant effect on the driving safety and long-term durability of bridges. To achieve the damage detection and localization of bridge deck pavement, a three-stage detection method based on the you-only-look-once v...
Image Processing, Computer-Assisted Deep Learning Rivers Algorithms China
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