Results 111 to 120 of about 219,190 (262)

Complex Versus Parsimonious Site‐Based Stochastic Ground Motion Models: Which One Is Better?

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Stochastic ground motion models (GMMs) provide a probabilistic representation of seismic input and are increasingly important for uncertainty quantification (UQ) in earthquake engineering. This study focuses on site‐based stochastic GMMs, which learn the statistical features of selected datasets of seismic records and generate statistically ...
Maijia Su, Mayssa Dabaghi, Marco Broccardo   +2 more
wiley   +1 more source

Hybrid Simulation–Machine Learning Surrogates for Coordinate‐Based Solar and Wind Energy Yield Assessment in Iraq: A Streamlit Decision‐Support Tool

Energy Science &Engineering, EarlyView.
This study integrates climatic simulations with machine learning to predict solar and wind energy across Iraq. Results show Random Forest excels for solar (R2 = 0.98) and neural networks for wind (R2 = 0.97), enabling a practical web tool for renewable energy planning. ABSTRACT Driven by the global shift away from fossil fuels, solar and wind resources
Bassam Musheer Kareem, Abdolsalam Ebrahimpour, Jafar Ghafouri, Roghayyeh Motallebzadeh   +3 more
wiley   +1 more source

Software with artificial intelligence-derived algorithms for detecting and analysing lung nodules in CT scans: systematic review and economic evaluation

Health Technology Assessment
Background Lung cancer is one of the most common types of cancer and the leading cause of cancer death in the United Kingdom. Artificial intelligence-based software has been developed to reduce the number of missed or misdiagnosed lung nodules on ...
Julia Geppert, Peter Auguste, Asra Asgharzadeh, Hesam Ghiasvand, Mubarak Patel, Anna Brown, Surangi Jayakody, Emma Helm, Dan Todkill, Jason Madan, Chris Stinton, Daniel Gallacher, Sian Taylor-Phillips, Yen-Fu Chen   +13 more
doaj   +1 more source

Analysis and Classification of Partial Shading Conditions in Photovoltaic Arrays

Energy Science &Engineering, EarlyView.
This study presents new mathematical models for describing P–V curve extrema under different shading scenarios and applies machine learning classifiers that use features derived from P–V characteristics for accurate fault identification. ABSTRACT With the escalating global transition toward renewable energy, ensuring the operational stability and ...
Hamid Reza Parsa, Mohammad Sarvi
wiley   +1 more source

Potential for use of Al/machine learning for pharmacovigilance: Is there a role for regulators?

British Journal of Clinical Pharmacology, EarlyView.
Christina Gao, Ashley M. Hopkins, Andrew Rowland, Stephen Bacchi   +3 more
wiley   +1 more source

Predicting Solar Photovoltaic Power Output in Saudi Arabia's Jazan Region: Performance Comparison of Machine Learning Models

Energy Science &Engineering, EarlyView.
Workflow of the PV power estimation and ML forecasting methodology. ABSTRACT Accurate prediction of solar panel energy output is vital for managing power systems effectively and maintaining a stable electrical grid. This is especially important in regions that rely heavily on renewable sources. This research provides a direct comparison of five machine
Abdoalateef Alzhrani, Abdullahi Abubakar Mas'ud, Mohd Khairul Amri Kamarudin, Firdaus Muhammad‐Sukki, Abdullahi Mohammad   +4 more
wiley   +1 more source

Smart Parking Systems: A Review of Optimization Techniques and Technological Advances

Energy Science &Engineering, EarlyView.
This review highlights optimization techniques and recent technological advances in smart parking systems, emphasizing their role in enhancing efficiency, reducing congestion, and improving user experience. It provides insights into innovative approaches that shape the future of sustainable and intelligent urban mobility. ABSTRACT In heavily populated,
Amirhossein Khosravi Sarvenoee, Mohammad Kohzadipour, Majid Valizadeh, Mohammad Saeedi Kia, Milad Karimian, Mohammad Sharifirad   +5 more
wiley   +1 more source

Artificial intelligence and liquidation: Reality, destiny and fantasy

International Insolvency Review, EarlyView.
Abstract Artificial intelligence (AI) is increasingly reshaping the administration of corporate liquidation. Beyond its established role in financial prediction and data analytics, AI is now assisting insolvency practitioners in identifying the onset of financial distress, managing creditor communications, tracing and valuing assets and enhancing ...
Kai Zhang, Jingchen Zhao
wiley   +1 more source

Optimizing feather hydrolysate via machine learning for microbial recycling of waste concrete fines

Journal of Chemical Technology &Biotechnology, EarlyView.
Abstract BACKGROUND The concrete industry faces significant challenges from CO2 emissions and the disposal of waste concrete fines (WCF). Microbially induced calcite precipitation (MICP) can bind WCF into bioconcrete, but the high cost of commercial culture media hinders its application.
Henrietta Ottová, Barbora Malíková, Václav Nežerka, Petr Holeček, Dana Koňáková, Hana Stiborová   +5 more
wiley   +1 more source

A talus rock glacier in Nantlle Valley, North Wales

Journal of Quaternary Science, EarlyView.
ABSTRACT Landforms comprising mixtures of fine and coarse sediment and deposited during late glacial times are ubiquitous in the British mountains. In many cases, their interpretation has often proved contentious; as a result, the non‐generic term discrete debris accumulations (DDA) has been used to describe them and, over the last 50 years, some have ...
Stephan Harrison, Ed Anderson
wiley   +1 more source