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Green AI: Transforming Energy Forecasting for a Sustainable Future

Researchers delve into the world of Green AI, a promising technology that combines artificial intelligence with sustainability practices to address energy forecasting and management challenges. The article explores applications in green energy load forecasting, power consumption prediction, and electricity price forecasting, highlighting the potential of Green AI to optimize energy distribution, promote renewable energy sources, and foster a greener and more sustainable future.

2 Aug 2023

Federated Learning as a Service: Enhancing Trustworthy AI in B5G/6G Networks

https://www.sciencedirect.com/science/article/pii/S0140366423002724?via%3Dihub

2 Aug 2023

AI-Driven Automated Discovery of Polymer Membranes for Carbon Capture

Researchers demonstrate an AI-driven automated workflow for discovering efficient polymer membranes for carbon capture, overcoming previous limitations. This approach combines generative design and physical validation, offering a computational screening alternative before lab validation. The study showcases the effectiveness of the proposed method, promising accelerated material discovery.

1 Aug 2023

Harnessing the Power of Machine Learning for Forest Fire Management: A Review

This comprehensive review explores the integration of machine learning (ML) techniques in forest fire science. The study highlights the significance of early fire prediction and detection for effective fire management. It discusses various ML methods applied in forest fire detection, prediction, fire mapping, and data evaluation. The review identifies challenges and research priorities while emphasizing the potential benefits of ML in improving forest fire resilience and enabling more efficient data analysis and modeling.

26 Jul 2023

Unveiling Drought Impacts: How Explainable Machine Learning Revolutionizes Prediction and Assessment

This study introduces an explainable machine learning (ML) pipeline that predicts and assesses complex drought impacts. By utilizing the XGBoost model and the SHAP model, researchers achieved superior performance in predicting multi-dimensional drought impacts compared to baseline models. The study emphasizes the importance of model explainability, as it enhances trust and enables stakeholders to better understand the relationships between drought impacts and indicators.

26 Jul 2023

Unveiling Housing Price Dynamics: XGBoost and SHAP Models Shed Light on Neighborhood Effects

Researchers employ XGBoost and SHAP models to uncover the nonlinear relationships between neighborhood characteristics and housing prices in Shanghai. The study provides valuable insights into the importance of public and private amenities, street views, and location in determining housing values, revolutionizing real estate market research and urban planning.

13 Jul 2023

Optimizing Sensor Placement: Forecasting Micro-Climates in Greenhouses Using Dense Neural Networks

A recent study presents a revolutionary framework that utilizes a multi-channeled dense neural network (DNN) to predict temperature and relative humidity values in a greenhouse cultivating strawberries. The framework determines optimal sensor locations without the need for relocation, providing accurate estimations of micro-climate conditions.

12 Jul 2023

Revolutionizing Artificial Neural Networks: Self-Powered In-Sensor ANNs with Molecular Ferroelectric Photomemristors

Researchers have achieved a breakthrough in the development of artificial neural networks (ANNs) by implementing self-powered in-sensor ANNs using molecular ferroelectric (MF)-based photomemristor arrays. These innovative devices enable real-time optical signal recognition and acquisition while minimizing power consumption.

12 Jul 2023

Powering Superconductivity with AI: Unlocking Potential and Overcoming Challenges

This article reviews the transformative impact of artificial intelligence (AI) techniques such as deep learning and machine learning in the field of superconductivity. From condition monitoring and design optimization to intelligent modeling and estimation, AI offers innovative solutions to overcome challenges, accelerate commercialization, and unlock new opportunities in the realm of superconducting technologies and materials.

10 Jul 2023