AIMC Topic: Chlorophyll A

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Classifiers based on artificial intelligence in the prediction of recently planted coffee cultivars using a Remotely Piloted Aircraft System.

Anais da Academia Brasileira de Ciencias Nov 3, 2023
The classification and prediction methods through artificial intelligence algorithms are applied in different sectors to assist and promote intelligent decision-making. In this sense, due to the great importance in the cultivation, consumption and ex...
Neural Networks, Computer Artificial Intelligence Algorithms Coffee Chlorophyll A
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Deep learning based soft-sensor for continuous chlorophyll estimation on decentralized data.

Water research Oct 14, 2023
Monitoring the concentration of pigments like chlorophyll (Chl) in water-bodies is a key task to contribute to their conservation. However, with the existing sensor technology, measurement in real-time and with enough frequency to ensure proper risk ...
Environmental Monitoring Chlorophyll Chlorophyll A Neural Networks, Computer Deep Learning
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Prediction and sensitivity analysis of chlorophyll a based on a support vector machine regression algorithm.

Environmental monitoring and assessment May 20, 2023
Outbreaks of planktonic algae seriously affect the water quality of rivers and are difficult to control. Based on the analysis of the temporal and spatial variation characteristics of environmental factors, this study uses a support vector machine re...
Chlorophyll Chlorophyll A Phosphorus China Rivers Eutrophication Environmental Monitoring Lakes Support Vector Machine Nitrogen
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Effects of nitrogen and phosphorus addition on growth and leaf nitrogen metabolism of alfalfa in alkaline soil in Yinchuan Plain of Hetao Basin.

PeerJ Apr 13, 2022
Alkaline soil is widely distributed in China. Its rational utilization is an effective measure to solve land shortage and improve the environment. Alfalfa is characterized by strong salt and alkali tolerance and high yield and protein content. Nitrog...
Transaminases Plants Amino Acids Phosphorus Chlorophyll A Nitrogen Nitrate Reductase Soil Medicago sativa
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Interpretation of ensemble learning to predict water quality using explainable artificial intelligence.

The Science of the total environment Apr 6, 2022
Algal bloom is a significant issue when managing water quality in freshwater; specifically, predicting the concentration of algae is essential to maintaining the safety of the drinking water supply system. The chlorophyll-a (Chl-a) concentration is a...
Machine Learning Algorithms Artificial Intelligence Water Quality Chlorophyll A
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Early warning of algal blooms based on the optimization support vector machine regression in a typical tributary bay of the Three Gorges Reservoir, China.

Environmental geochemistry and health Mar 10, 2022
Algal blooms caused by climate change and human activities have received considerable attention in recent years. Since chlorophyll a (Chl-a) can be used as an indicator of phytoplankton biomass, it has been selected as a direct indicator for monitori...
Bays Eutrophication China Support Vector Machine Chlorophyll A Humans Artificial Intelligence
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LSTM Networks to Improve the Prediction of Harmful Algal Blooms in the West Coast of Sabah.

International journal of environmental research and public health Jul 19, 2021
Harmful algal bloom (HAB) events have alarmed authorities of human health that have caused severe illness and fatalities, death of marine organisms, and massive fish killings. This work aimed to perform the long short-term memory (LSTM) method and co...
Harmful Algal Bloom Chlorophyll A Humans Animals Neural Networks, Computer Malaysia
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Monitoring the vertical distribution of HABs using hyperspectral imagery and deep learning models.

The Science of the total environment Jun 19, 2021
Remote sensing techniques have been applied to monitor the spatiotemporal variation of harmful algal blooms (HABs) in many inland waters. However, these studies have been limited to monitor the vertical distribution of HABs due to the optical complex...
Harmful Algal Bloom Chlorophyll Chlorophyll A Phycocyanin Deep Learning Environmental Monitoring
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Deep learning based regression for optically inactive inland water quality parameter estimation using airborne hyperspectral imagery.

Environmental pollution (Barking, Essex : 1987) Jun 6, 2021
Airborne hyperspectral remote sensing has the characteristics of high spatial and spectral resolutions, and provides an opportunity for accurate and efficient inland water qauality monitoring. Many studies have focused on evaluating and quantifying t...
Chlorophyll A Water Quality Deep Learning Rivers Environmental Monitoring
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Quantification of chlorophyll-a in typical lakes across China using Sentinel-2 MSI imagery with machine learning algorithm.

The Science of the total environment Mar 8, 2021
Lake eutrophication has attracted the attention of the government and general public. Chlorophyll-a (Chl-a) is a key indicator of algal biomass and eutrophication. Many efforts have been devoted to establishing accurate algorithms for estimating Chl-...
Chlorophyll China Algorithms Artificial Intelligence Chlorophyll A Environmental Monitoring Eutrophication Ecosystem Lakes
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