AIMC Topic: Rivers

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Implementation of data intelligence models coupled with ensemble machine learning for prediction of water quality index.

Environmental science and pollution research international Jul 20, 2020
In recent decades, various conventional techniques have been formulated around the world to evaluate the overall water quality (WQ) at particular locations. In the present study, back propagation neural network (BPNN) and adaptive neuro-fuzzy inferen...
Machine Learning Intelligence Water Quality Rivers India Fuzzy Logic
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Exploring the multiscale hydrologic regulation of multipond systems in a humid agricultural catchment.

Water research Jul 11, 2020
Assessing the hydrologic processes over scales ranging from single wetland to regional is critical to understand the hydrologically-driven ecosystem services especially nutrient buffering of wetlands. Here, we present a novel approach to quantify the...
Rivers Hydrology China Agriculture Artificial Intelligence Ecosystem
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The Analysis of the Urban Sprawl Measurement System of the Yangtze River Economic Belt, Based on Deep Learning and Neural Network Algorithm.

International journal of environmental research and public health Jun 12, 2020
In the context of rapid urbanization, the spread of cities in the Yangtze River Economic Belt is intensifying, which has an impact on the green and sustainable development of these cities. It is necessary to establish an accurate urban sprawl measure...
Neural Networks, Computer Cities Rivers Urbanization Deep Learning China
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Assessing the biochemical oxygen demand using neural networks and ensemble tree approaches in South Korea.

Journal of environmental management Jun 5, 2020
The biochemical oxygen demand (BOD), one of widely utilized variables for water quality assessment, is metric for the ecological division in rivers. Since the traditional approach to predict BOD is time-consuming and inaccurate due to inconstancies i...
Water Quality Environmental Monitoring Rivers Oxygen Neural Networks, Computer Biological Oxygen Demand Analysis Republic of Korea
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Explore the relationship between fish community and environmental factors by machine learning techniques.

Environmental research Feb 17, 2020
In the face of multiple habitat alterations originating from both natural and anthropogenic factors, the fast-changing environments pose significant challenges for maintaining ecosystem integrity. Machine learning is a powerful tool for modeling comp...
Conservation of Natural Resources Fishes Rivers Animals Ecosystem Taiwan Population Dynamics Environmental Monitoring Neural Networks, Computer Machine Learning
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Letter to the editor "Modeling daily suspended sediment load using improved support vector machine model and genetic algorithm".

Environmental science and pollution research international Feb 14, 2020
Rivers Geologic Sediments Support Vector Machine
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Hybrid decision tree-based machine learning models for short-term water quality prediction.

Chemosphere Feb 11, 2020
Water resources are the foundation of people's life and economic development, and are closely related to health and the environment. Accurate prediction of water quality is the key to improving water management and pollution control. In this paper, t...
Water Quality Rivers Environmental Monitoring Oxygen Temperature Models, Statistical Water Pollution Water Decision Trees Humans Machine Learning
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A Machine Learning Ensemble Approach Based on Random Forest and Radial Basis Function Neural Network for Risk Evaluation of Regional Flood Disaster: A Case Study of the Yangtze River Delta, China.

International journal of environmental research and public health Dec 19, 2019
The Yangtze River Delta (YRD) is one of the most developed regions in China. This is also a flood-prone area where flood disasters are frequently experienced; the situations between the people-land nexus and the people-water nexus are very complicate...
Rivers Floods Cities Forests Geographic Information Systems China Machine Learning Neural Networks, Computer Ecosystem Risk Assessment
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Valuation methodology of laminar erosion potential using fuzzy inference systems in a Brazilian savanna.

Environmental monitoring and assessment Sep 7, 2019
This study presents an approach on the evaluation of potential laminar erosion in the Ribeirão Sucuri Grande watershed. It is located in the northeast of the state of Goiás, Brazil, a conservation area under strong anthropogenic pressure. A Mamdani f...
Conservation of Natural Resources Grassland Brazil Fuzzy Logic Soil Water Movements Rivers Environmental Monitoring
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Assessment of River Water Quality Based on an Improved Fuzzy Matter-Element Model.

International journal of environmental research and public health Aug 5, 2019
In this paper, an improved fuzzy matter-element (IFME) method was proposed, which integrates the classical matter-element (ME) method, set pair analysis (SPA), and variable coefficient method (VCM). The method was applied to evaluate water quality of...
Water Quality Water Pollutants, Chemical Rivers China Fuzzy Logic Environmental Monitoring
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