AIMC Topic: Rivers

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Water quality prediction based on recurrent neural network and improved evidence theory: a case study of Qiantang River, China.

Environmental science and pollution research international May 15, 2019
Water quality prediction is an effective method for managing and protecting water resources by providing an early warning against water quality deterioration. In general, the existing water quality prediction methods are based on a single shallow mod...
Neural Networks, Computer Environmental Monitoring Water Quality Rivers Forecasting China Models, Theoretical
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Do reductions in agricultural field drainage during the growing season impact bacterial densities and loads in small tile-fed watersheds?

Water research Nov 30, 2018
Predicting bacterial levels in watersheds in response to agricultural beneficial management practices (BMPs) requires understanding the germane processes at both the watershed and field scale. Controlling subsurface tile drainage (CTD) is a highly ef...
Bacteria Agriculture Escherichia coli Seasons Rivers
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Performance assessment of artificial neural networks and support vector regression models for stream flow predictions.

Environmental monitoring and assessment Nov 8, 2018
Water resources planning, development, and management need reliable forecasts of river flows. In past few decades, an important dimension has been introduced in the prediction of the hydrologic phenomenon through artificial intelligence-based modelin...
Environmental Monitoring Support Vector Machine Pakistan Neural Networks, Computer Artificial Intelligence Algorithms Hydrology Rivers Water Movements
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Modeling daily water temperature for rivers: comparison between adaptive neuro-fuzzy inference systems and artificial neural networks models.

Environmental science and pollution research international Nov 7, 2018
River water temperature is a key control of many physical and bio-chemical processes in river systems, which theoretically depends on multiple factors. Here, four different machine learning models, including multilayer perceptron neural network model...
Water Quality Rivers Cluster Analysis Models, Chemical Algorithms Neural Networks, Computer Water Temperature Machine Learning Environmental Monitoring Fuzzy Logic
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Priorization of River Restoration by Coupling Soil and Water Assessment Tool (SWAT) and Support Vector Machine (SVM) Models in the Taizi River Basin, Northern China.

International journal of environmental research and public health Sep 23, 2018
Identifying priority zones for river restoration is important for biodiversity conservation and catchment management. However, limited data due to the difficulty of field collection has led to research to better understand the ecological status withi...
Seasons Rivers Soil Hydrology Environmental Restoration and Remediation Animals Environmental Monitoring Aquatic Organisms China Support Vector Machine Biodiversity
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Algal Bloom Prediction Using Extreme Learning Machine Models at Artificial Weirs in the Nakdong River, Korea.

International journal of environmental research and public health Sep 21, 2018
In this study, we design an intelligent model to predict chlorophyll-a concentration, which is the primary indicator of algal blooms, using extreme learning machine (ELM) models. Modeling algal blooms is important for environmental management and eco...
Rivers Harmful Algal Bloom Chlorophyll Republic of Korea Environmental Monitoring Neural Networks, Computer Machine Learning
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Four Major South Korea's Rivers Using Deep Learning Models.

International journal of environmental research and public health Jun 24, 2018
Harmful algal blooms are an annual phenomenon that cause environmental damage, economic losses, and disease outbreaks. A fundamental solution to this problem is still lacking, thus, the best option for counteracting the effects of algal blooms is to ...
Water Quality Rivers Harmful Algal Bloom Republic of Korea Deep Learning Models, Biological
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Use of ultraviolet-visible spectrophotometry associated with artificial neural networks as an alternative for determining the water quality index.

Environmental monitoring and assessment May 2, 2018
The water quality index (WQI) is an important tool for water resource management and planning. However, it has major disadvantages: the generation of chemical waste, is costly, and time-consuming. In order to overcome these drawbacks, we propose to s...
Water Pollutants, Chemical Principal Component Analysis Neural Networks, Computer Brazil Environmental Monitoring Spectrophotometry, Ultraviolet Water Pollution, Chemical Ultraviolet Rays Water Quality Rivers
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Risk Analysis of Earth-Rock Dam Failures Based on Fuzzy Event Tree Method.

International journal of environmental research and public health Apr 29, 2018
Earth-rock dams make up a large proportion of the dams in China, and their failures can induce great risks. In this paper, the risks associated with earth-rock dam failure are analyzed from two aspects: the probability of a dam failure and the result...
Hydrodynamics Engineering Humans Fuzzy Logic China Equipment Failure Rivers
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Ecological Vulnerability Assessment Based on Fuzzy Analytical Method and Analytic Hierarchy Process in Yellow River Delta.

International journal of environmental research and public health Apr 25, 2018
The Yellow River Delta (YRD), located in Yellow River estuary, is characterized by rich ecological system types, and provides habitats or migration stations for wild birds, all of which makes the delta an ecological barrier or ecotone for inland area...
Rivers Conservation of Natural Resources Fuzzy Logic Plants Weather Humans Soil Ecosystem China Models, Theoretical Environmental Monitoring
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