Climate Change News and Research

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AI Extends EV Battery Life

Researchers developed a domain knowledge-guided machine learning framework that accurately estimates the state of health of lithium-ion batteries, achieving high precision even with limited data, to advance electric vehicle technologies.

18 Nov 2024

Machine Learning Powering Breakthroughs in Climate Forecasting and Modeling

Machine learning is transforming climate science by enhancing data reconstruction, improving model precision, and enabling more accurate climate forecasts at lower costs.

14 Nov 2024

AI Reconstructs Europe’s Climate Extremes, Transforming Climate Risk Analysis

AI reconstructs historical climate extremes in Europe from 1901 to 2018, filling data gaps and enhancing climate risk assessment.

4 Nov 2024

Researchers Develop AI System to Predict and Control Extreme Turbulence in UAVs

Researchers at Caltech and Nvidia have developed FALCON, a model-based AI that predicts turbulent winds and stabilizes UAVs in real-time using reinforcement learning.

16 Oct 2024

AI Transforms Climate Research, China Leads Global Innovation

Researchers used a vast, multilingual dataset to systematically review how artificial intelligence is applied in global climate research, identifying China as the leading contributor and uncovering opportunities for AI to further impact climate science.

3 Oct 2024

Green AI: Exploring Sustainable Strategies for Energy-Efficient Systems and Eco-Friendly Innovations

Researchers explore green AI as a key approach to minimizing AI's environmental impact through energy-efficient algorithms and hardware, driving sustainability without sacrificing performance.

27 Sep 2024

AI-Generated Videos Implant False Memories, Distorting Human Recollections

AI-generated images and videos significantly increase false memories, with AI-generated videos causing the strongest memory distortions. This raises concerns for legal, ethical, and societal impacts.

18 Sep 2024

Deep Learning Advances Deep-Sea Biota Identification in the Great Barrier Reef

Researchers developed the "Deepdive" dataset and benchmarked deep learning models to automate the classification of deep-sea biota in the Great Barrier Reef, achieving significant accuracy with the Inception-ResNet model.

8 Sep 2024

Machine Learning Enhances Water Quality Monitoring

This study uses machine learning algorithms and satellite imagery to estimate dissolved oxygen levels in Baiyangdian Lake. The approach, particularly the Extra Tree Regression model, offers rapid, accurate water quality monitoring, outperforming traditional methods in urban water bodies.

30 Aug 2024

Scientometric Analysis Maps ML Trends in Water Prediction

This research reviews 876 articles on water prediction, showcasing the evolution of ML and DL techniques and highlighting significant contributors and trends.

23 Aug 2024

ML Predicts Urban Heat from Land Use Changes

Using machine learning algorithms, researchers analyzed land use changes in Kabul from 1998 to 2022 and their impact on land surface temperature. The study projected significant increases in built-up areas and high-temperature zones by 2046, highlighting urbanization's climatic effects.

22 Aug 2024

ML Models Predict Wind-Solar Power Output

The study compared various machine-learning models for predicting wind-solar tower power output. While linear regression was inadequate, polynomial regression and deep neural networks (DNN) showed improved accuracy. The DNN model outperformed others, demonstrating high prediction accuracy and efficiency for renewable energy forecasting.

6 Aug 2024

AI Enhances Building Efficiency and Cuts Emissions

Researchers evaluated AI's potential to reduce energy consumption and emissions in US medium office buildings. Their study demonstrated that AI could significantly enhance building energy efficiency, achieving up to a 21% reduction in energy use and substantial carbon emissions reductions by 2050, particularly when combined with supportive energy policies and low-carbon power sources.

29 Jul 2024

Predictive Model for Tea Anthracnose in Yunnan

Researchers developed a rapid, non-destructive prediction model for tea anthracnose in Yunnan using IoT climate data and advanced statistical techniques. The LASSO-COX-NOMOGRAM model demonstrated high accuracy, outperforming traditional methods, and revealed significant correlations between 21 environmental factors and disease severity, enhancing early detection and eco-friendly management practices in tea production.

21 Jul 2024

Predicting Rice Production with Precision Using AI

Researchers in Scientific Reports introduced an AI-based approach to predict rice production in China using multi-source data. Hybrid models, particularly RF-XGB, outperformed single models in accuracy, emphasizing the importance of soil properties and sown area over climate variables in determining rice yields.

8 Jul 2024

Optimal Sensor Placement Enhances Digital Twins in Water Systems

Researchers introduced a novel methodology for optimal sensor placement in water infrastructure to enhance digital twins. Utilizing a graph neural network-based metamodel, the approach effectively estimated pressure at consumption nodes, demonstrating accurate and efficient sensor configurations through tests on a synthetic case study.

5 Jul 2024

AI Models Enhance Energy Efficiency in Desert Climates

Researchers developed and compared three AI models to estimate energy consumption in residential buildings in desert climates, identifying key factors influencing energy use. The study highlights AI's potential to improve energy efficiency and sustainability in the built environment.

21 Jun 2024

GCCMP Dataset: AI-Powered Climate Policy Analysis

Researchers introduced the global climate change mitigation policy dataset (GCCMPD), created using a semi-supervised hybrid machine learning approach to classify 73,625 policies across 216 entities. This comprehensive dataset aims to aid policymakers and researchers by offering detailed insights into climate mitigation efforts, enhancing the understanding of global climate activities.

12 Jun 2024

AI-Driven Green Power Trading Boosts China's Energy Market

This study introduced a novel green power certificate trading system in China, utilizing Q-learning, smart contracts, and multi-agent Nash strategies to enhance efficiency and collaboration. The innovative framework increased trading prices by 20% and transaction success rates by 30-fold, significantly advancing China's renewable energy goals and supporting carbon neutrality targets.

22 May 2024

Carrot Quality Assessment Using Hyperspectral Imaging and Multivariate Analysis

Through hyperspectral imaging (HSI) and multivariate analysis, researchers accurately predicted pH and carotenoid content in carrots, crucial for nutritional assessment. Models utilizing partial least squares regression (PLSR) and least squares support vector machine (LS-SVM) showed LS-SVM's superiority in pH prediction and carotenoid content, offering a promising approach for internal quality evaluation in carrots.

22 Apr 2024