AIMC Topic: Wetlands

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Tree-structured parzen estimator optimized-automated machine learning assisted by meta-analysis for predicting biochar-driven NO mitigation effect in constructed wetlands.

Journal of environmental management Feb 17, 2024
Biochar is a carbon-neutral tool for combating climate change. Artificial intelligence applications to estimate the biochar mitigation effect on greenhouse gases (GHGs) can assist scientists in making more informed solutions. However, there is also e...
Machine Learning Soil Artificial Intelligence Wetlands Nitrous Oxide Nitrogen Charcoal
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Machine learning predicts which rivers, streams, and wetlands the Clean Water Act regulates.

Science (New York, N.Y.) Jan 25, 2024
We assess which waters the Clean Water Act protects and how Supreme Court and White House rules change this regulation. We train a deep learning model using aerial imagery and geophysical data to predict 150,000 jurisdictional determinations from the...
Drinking Water Rivers Wetlands Water Pollution Conservation of Natural Resources Water Quality Machine Learning
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Wetland Ecotourism Development Using Deep Learning and Grey Clustering Algorithm from the Perspective of Sustainable Development.

Journal of environmental and public health Aug 4, 2022
The purpose is to promote the sustainable development of wetland ecotourism in China and plan the passenger flow in different tourism periods. This work selects Zhangye Heihe wetland ecotourism spot as the research object. Firstly, the two single wet...
Wetlands Sustainable Development Algorithms Deep Learning Cluster Analysis
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Extracting Wetland Type Information with a Deep Convolutional Neural Network.

Computational intelligence and neuroscience May 18, 2022
Wetlands have important ecological value. The application of wetland remote sensing is essential for the timely and accurate analysis of the current situation in wetlands and dynamic changes in wetland resources, but high-resolution remote sensing im...
Wetlands Remote Sensing Technology Neural Networks, Computer
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A new deep learning approach based on bilateral semantic segmentation models for sustainable estuarine wetland ecosystem management.

The Science of the total environment May 10, 2022
Nowadays, estuarial areas have been strongly affected by the construction of electrical power dams from upstream, downstream urbanization and many types of hazards along the coastal regions. It has resulted in significant changes in estuarine wetland...
Ecosystem Deep Learning Wetlands Estuaries Conservation of Natural Resources Semantics
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Performance comparison of deep learning and machine learning methods in determining wetland water areas using EuroSAT dataset.

Environmental science and pollution research international Nov 8, 2021
Wetlands are critical to the ecology because they maintain biodiversity and provide home for a variety of species. Researching, mapping, and conservation of wetlands is a challenging and time-consuming process. Because they produce temporal and geogr...
Water Deep Learning Neural Networks, Computer Wetlands Support Vector Machine Machine Learning
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Developing a new approach for design support of subsurface constructed wetland using machine learning algorithms.

Journal of environmental management Oct 7, 2021
Knowing the effluent quality of treatment systems in advance to enable the design of treatment systems that comply with environmental standards is a realistic strategy. This study aims to develop machine learning - based predictive models for designi...
Machine Learning Nitrogen Algorithms Wetlands
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Machine learning models for wetland habitat vulnerability in mature Ganges delta.

Environmental science and pollution research international Jan 4, 2021
The present study attempts to measure wetland habitat vulnerability (WHV) in the Indian part of mature Ganges delta. Predictive algorithms belonging to bivariate statistics and machine learning (ML) algorithms were applied for fulfilling the data min...
Wetlands Algorithms Ecosystem Machine Learning
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Mangrove forest classification and aboveground biomass estimation using an atom search algorithm and adaptive neuro-fuzzy inference system.

PloS one May 21, 2020
BACKGROUND: Advances in earth observation and machine learning techniques have created new options for forest monitoring, primarily because of the various possibilities that they provide for classifying forest cover and estimating aboveground biomass...
Wetlands Biomass Models, Biological Vietnam Support Vector Machine
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Artificial intelligence based approaches to evaluate actual evapotranspiration in wetlands.

The Science of the total environment Nov 20, 2019
Wetlands are extraordinary ecosystems and important climate regulators that also contribute to reduce natural disaster risk. Unfortunately, wetlands are declining much faster than forests. The safeguarding of the wetlands also needs knowledge of the ...
Water Movements Wetlands Artificial Intelligence Wind Environmental Monitoring Neural Networks, Computer Models, Theoretical Temperature
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