Interpretable temporal-spatial graph attention network for multi-site PV power forecasting

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Monitoring of cardiac output (CO) is a mainstay of hemodynamic management in the acutely or critically ill patient. Invasive determination of CO using thermodilution, albeit regarded as the gold standard, is cumbersome and bears risks inherent to catheteri ...

Accurate forecasting of photovoltaic (PV) power production is crucial for the integration of more renewable energy sources into the power grid. PV power production is highly intermittent, due to the stochastic cloud behaviour and cloud dynamics. Previous w ...

This paper introduces a novel architecture for Quantum Graph Neural Networks, which is significantly different from previous approaches found in the literature. The proposed approach produces similar outcomes with respect to previous models but with fewer ...

Solar photovoltaics (PV) is one of the most competitive renewable energy technologies in order to meet the increasing global energy demand and decrease CO2 emissions by competing effectively with fossil fuels. One of the important applications of PV energy ...

This study presents an augmented hybrid approach for improving the diagnosis of malignant skin lesions by combining convolutional neural network (CNN) predictions with selective human interventions based on prediction confidence. The algorithm retains high ...

Like many other countries, Switzerland offers various incentives to promote residential solar PV, but not all households have equal access to them. Using a microsimulation approach based on merged data from the Swiss Household Budget Survey and Household E ...

Estimating ecosystem-atmosphere fluxes such as evapotranspiration (ET) in a robust manner and at a global scale remains a challenge. Methods based on machine learning (ML) have shown promising results in achieving such upscaling, providing a complementary ...

The 2D/3D or 2D/quasi-2D composite mixed-dimensional construction of hybrid perovskite interfaces is gaining increasing attention due to their enhanced stability toward degradation without compromising the corresponding solar cell efficiency. Much of this ...

The electrification of the transport sector is a key element in decarbonizing our societies. However, energy systems will have to cope with additional electricity demand due to the charging needs of electric vehicles (EVs) together with the integration of ...

More attention has been paid to integrating existing knowledge with data to understand the complex mechanical behaviour of geomaterials, but it incurs scepticism and criticism on its generalizability and robustness. Moreover, a common mistake in current da ...

The recent geopolitical conflicts in Europe have underscored the vulnerability of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy systems ensuring sustainable energy supply in the future, the ...

As the demand for high channel counts and high-resolution recordings of neural activity continues to grow, the increased power and data rate generated impose hard constraints on the telemetry capabilities of wireless implantable neural interfaces. To addre ...

Because building-integrated photovoltaic (BIPV) modules are fully integrated into a building envelope, the back of the module can be exposed to little or no ventilation, resulting in increased operating temperatures. As the temperature increases, the perfo ...

To retrieve Surface Solar Radiation (SSR) from satellite images, a baseline reflectance of the observed ground in clear-sky conditions, also called background reflectance, is necessary to distinguish atmospheric absorption and scattering effects from surfa ...

Cesium-formamidinium lead iodide (CsxFA1-xPbI3) perovskites are a promising methylammonium-free alternative for efficient single-junction solar cells. However, they have not been fully explored by vapor-phase deposition techniques. Herein, a template-assis ...

This study integrates deep learning and geospatial analysis to enhance soil loss estimation in the Moulouya Watershed, a region prone to erosion due to diverse topography and climatic conditions. Traditional models like the Universal Soil Loss Equation (US ...

The first two chapters develop ML-based models that generate conditional SDF estimates efficiently using conditioning information sets, resulting in minimal pricing errors and superior Sharpe ratios compared to traditional conditional asset pricing models. ...

This thesis uses femtosecond laser spectroscopy in studying strong correlation in condensed matters that are pertinent to future technology: a wide bandgap perovskite and a quantum material, with the employment of ultrafast time-resolved spectroscopy in th ...

Driving continuous, low-power artificial intelligence (AI) in the Internet of Things (IoT) requires reliable energy harvesting and storage under indoor or low-light conditions, where batteries face constraints such as finite lifetimes and increased environ ...

The European Union's Green Deal aims for a 55% reduction in greenhouse gas emissions by 2030. To reach this goal, a massive integration of Renewable Energy Sources (RES) into the power grid is necessary. As RES become a large part of the electricity genera ...

Interpretable temporal-spatial graph attention network for multi-site PV power forecasting

Chat with Graph Search

Machine learning-enabled estimation of cardiac output from peripheral waveforms is independent of blood pressure measurement location in an in silico population

Network time series forecasting in photovoltaics power production

A Study on Quantum Graph Neural Networks Applied to Molecular Physics

Reliability and Long-term Performance of Building Integrated Photovoltaic (BIPV) Modules

Enhancing skin lesion classification: a CNN approach with human baseline comparison

Distributional justice, effectiveness, and costs of current and alternative solar PV incentive schemes in Switzerland

On the added value of sequential deep learning for the upscaling of evapotranspiration

Tuning Electronic and Optical Properties of 2D/3D Interfaces of Hybrid Perovskites through Interfacial Charge Transfer: Prediction of Higher-Efficiency Interface Solar Cells Using Hybrid-DFT Methods

From PV to EV: Mapping the Potential for Electric Vehicle Charging with Solar Energy in Europe

t-PiNet: A thermodynamics-informed hierarchical learning for discovering constitutive relations of geomaterials

Identification of typical district configurations: A two-step global sensitivity analysis framework

A Reconfigurable High-Dynamic Range ∆Σ Front-End with Event-Based Decimation for Bandwidth-Efficient Implantable Neural Interfaces

Correlating long-term performance and aging behaviour of building integrated PV modules

Retrieval of Surface Solar Radiation through Implicit Albedo Recovery from Temporal Context

Template-Assisted Growth of CsxFA1-xPbI3 with Pulsed Laser Deposition for Single Junction Perovskite Solar Cells

Application of Deep Learning and Geospatial Analysis in Soil Loss Risk in the Moulouya Watershed, Morocco

Machine Learning Applications to Conditional Asset Pricing: Attention, CNNs, and Neural Tangent Kernels

Investigating Non-equilibrium Physics in Wide Bandgap Semiconductors and Quantum Materials via Ultrafast Spectroscopy

Unlocking high-performance photocapacitors for edge computing in low-light environments

Advanced control strategies to exploit the hydropower potential enhancing ancillary services provision to the power system