AIMC Topic: Climate Change

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Forecasting carbon emissions from energy consumption in Guangdong Province, China with a novel grey multivariate model.

Environmental science and pollution research international Apr 6, 2022
Carbon dioxide has a significant impact on global climate change due to its natural greenhouse effect. The objective and credible forecast of carbon emissions is very important for the government to formulate and implement the corresponding emission ...
Neural Networks, Computer Carbon Dioxide Climate Change Forecasting China
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Predicting the impact of climate change on the re-emergence of malaria cases in China using LSTMSeq2Seq deep learning model: a modelling and prediction analysis study.

BMJ open Mar 31, 2022
OBJECTIVES: Malaria is a vector-borne disease that remains a serious public health problem due to its climatic sensitivity. Accurate prediction of malaria re-emergence is very important in taking corresponding effective measures. This study aims to i...
China Malaria Humans Deep Learning Climate Change Malaria, Falciparum
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Deep learning shows declining groundwater levels in Germany until 2100 due to climate change.

Nature communications Mar 9, 2022
In this study we investigate how climate change will directly influence the groundwater resources in Germany during the 21 century. We apply a machine learning groundwater level prediction approach based on convolutional neural networks to 118 sites ...
Deep Learning Germany Groundwater Climate Change
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Deep Learning and Transformer Approaches for UAV-Based Wildfire Detection and Segmentation.

Sensors (Basel, Switzerland) Mar 3, 2022
Wildfires are a worldwide natural disaster causing important economic damages and loss of lives. Experts predict that wildfires will increase in the coming years mainly due to climate change. Early detection and prediction of fire spread can help red...
Fires Climate Change Deep Learning Wildfires
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Identifying climate thresholds for dominant natural vegetation types at the global scale using machine learning: Average climate versus extremes.

Global change biology Feb 24, 2022
The global distribution of vegetation is largely determined by climatic conditions and feeds back into the climate system. To predict future vegetation changes in response to climate change, it is crucial to identify and understand key patterns and p...
Temperature Climate Change Forecasting Machine Learning
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Confronting Deep-Learning and Biodiversity Challenges for Automatic Video-Monitoring of Marine Ecosystems.

Sensors (Basel, Switzerland) Jan 10, 2022
With the availability of low-cost and efficient digital cameras, ecologists can now survey the world's biodiversity through image sensors, especially in the previously rather inaccessible marine realm. However, the data rapidly accumulates, and ecolo...
Biodiversity Video Recording Climate Change Ecosystem Deep Learning
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A hybrid machine-learning model to map glacier-related debris flow susceptibility along Gyirong Zangbo watershed under the changing climate.

The Science of the total environment Nov 22, 2021
Gyirong serves as an important channel to Chine-Nepal Economic Corridor, which is also the only land route for China-Nepal trade since the 2015 earthquake. However, the Gyirong corridor suffers from glacier-related debris flow from every April to Sep...
Climate Change Ice Cover Support Vector Machine Machine Learning Logistic Models
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Combining novel technologies with interdisciplinary basic research to enhance horticultural crops.

The Plant journal : for cell and molecular biology Nov 10, 2021
Horticultural crops mainly include fruits, vegetables, ornamental trees and flowers, and tea trees (Melaleuca alternifolia). They produce a variety of nutrients for the daily human diet in addition to the nutrition provided by staple crops, and some ...
Horticulture Artificial Intelligence Computational Biology Nutrients Trees Crops, Agricultural Bioengineering Plant Breeding Interdisciplinary Research Flowers Fruit Climate Change Vegetables
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BERTtoCNN: Similarity-preserving enhanced knowledge distillation for stance detection.

PloS one Sep 10, 2021
In recent years, text sentiment analysis has attracted wide attention, and promoted the rise and development of stance detection research. The purpose of stance detection is to determine the author's stance (favor or against) towards a specific targe...
Climate Change Language Neural Networks, Computer Attitude Databases as Topic Models, Theoretical Knowledge
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Interpretable and explainable AI (XAI) model for spatial drought prediction.

The Science of the total environment Aug 21, 2021
Accurate prediction of any type of natural hazard is a challenging task. Of all the various hazards, drought prediction is challenging as it lacks a universal definition and is getting adverse with climate change impacting drought events both spatial...
Algorithms Climate Change Artificial Intelligence Droughts Meteorology
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