Results 221 to 230 of about 236,656 (279)

Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN

Deep Underground Science and Engineering, EarlyView.
A data preprocessing workflow is proposed to address challenges in rockburst data analysis. Coupled algorithms preprocess the data set, and hyperband optimization is used to enhance RNN performance. Results show that preprocessing improves accuracy, while dense layers enhance model stability and prediction performance.
Yong Fan, Chenxi Yin, Guangdong Yang, Shengyong Ding, Bin Tian   +4 more
wiley   +1 more source

Tuning Deep Learning for Predicting Aluminum Prices Under Different Sampling: Bayesian Optimization Versus Random Search. [PDF]

Entropy (Basel)
Antonio Figueroa AE, Lahmiri S.
europepmc   +1 more source

Real‐time monitoring of tunnel structures using digital twin and artificial intelligence: A short overview

Deep Underground Science and Engineering, EarlyView.
How artificial intelligence (AI) and digital twin (DT) technologies are revolutionizing tunnel surveillance, offering proactive maintenance strategies and enhanced safety protocols. It explores AI's analytical power and DT's virtual replicas of infrastructure, emphasizing their role in optimizing maintenance and safety in tunnel management.
Mohammad Afrazi, Danial Jahed Armaghani, Hossein Afrazi, Hadi Fattahi, Pijush Samui   +4 more
wiley   +1 more source

Advocating the potential of artificial intelligence for syndrome discovery in syndromic surveillance systems: A scoping review. [PDF]

iScience
Gomes Ferreira AP, Anžel A, Ullrich A, Hattab G.   +3 more
europepmc   +1 more source

A review on rockburst prediction and prevention to shape an ontology‐based framework for better decision‐making for underground excavations

Deep Underground Science and Engineering, EarlyView.
A scientometric analysis of 2449 journal articles and a comprehensive review of 336 papers were conducted, discussing and identifying challenges and research gaps in rockburst prediction and prevention and proposing an ontology‐based framework for better decision‐making in underground excavations. Abstract With underground engineering projects becoming
Hongchuan Yan, Haijiang Li, Hongqiang Xie, Mingli Xiao, Jianliang Pei, Huaizhong Liu, Jiangda He   +6 more
wiley   +1 more source

Research progress and current status of dynamic wave propagation characteristics in rock mass: A review

Deep Underground Science and Engineering, EarlyView.
This review elucidates the velocity–dispersion–attenuation coupling mechanisms of wave propagation in rock masses, compares six representative models, and reveals how pressure, temperature, mineral composition, and anisotropy jointly control dynamic responses in complex geological media.
Jiajun Shu, Tao Li, Ruiqi Yuan, Yue Li, Bingni Wu, Bo Liu, Zhengding Deng, Galindo Rubén, Fausto Molina‐Gómez   +8 more
wiley   +1 more source

AI-driven multimodal imaging fusion using swin transformer and optimized tensor fusion networks for pneumonia detection. [PDF]

Sci Rep
Sikindar S, Raghavendran CV, Madhavi G.
europepmc   +1 more source

Harnessing the power of machine and deep learning for transferring joint species distribution models considering the structure of biotic interactions

Ecography, EarlyView.
The transferability of single or joint species distribution models ((j)SDMs) depends on their ability to predict beyond the observed environmental range and to remain consistent despite shifts in biotic interactions. Transfer accuracy may be improved by recent advances in the application of deep learning that provide greater flexibility and potentially
Marco Basile, Maximilian Pichler, Francesco Valerio, Lorenzo Balducci, Francesco Chianucci, Sérgio Godinho, Francesco Rota, Frédéric Archaux, Christophe Bouget, Gediminas Brazaitis, Thomas Campagnaro, Ettore D'Andrea, Luc De Keersmaeker, Wouter Dekoninck, Pallieter De Smedt, Zoltán Elek, Itziar García‐ Mijangos, Frédéric Gosselin, Marion Gosselin, Andrin Gross, Elena Haeler, Sebastian Kepfer‐ Rojas, Nathalie Korboulewsky, Daniel Kozák, Thibault Lachat, Carlos Miguel Landivar Albis, Anja Leyman, Xiang Liu, Anders Mårell, Radim Matula, Martin Mikoláš, Péter Ódor, Yoan Paillet, Kastytis Šimkevičius, Tommaso Sitzia, Silvia Stofer, Nicolas Strebel, Miroslav Svoboda, Flóra Tinya, Mariana Ujházyová, Kris Vandekerkhove, Kris Verheyen, Michael Wohlwend, Fotios Xystrakis, Sabina Burrascano   +44 more
wiley   +1 more source

Enhancing heat and mass transfer in hybrid nanofluid with gyrotactic microbes and local thermal non equlibrium effects using artificial neural network. [PDF]

Discov Nano
Aoudia M, Benabdallah F, Khan MS, Khan I, Abbas M.   +4 more
europepmc   +1 more source

Ictal–interictal continuum and status epilepticus: Two sides of the same coin? A prospective magnetic resonance imaging study

Epilepsia, EarlyView.
Abstract Objective Status epilepticus (SE) is the most severe expression of seizures, encompassing both SE with prominent motor symptoms and nonconvulsive SE (NCSE). Ictal–interictal continuum (IIC), an electroencephalographic phenomenon, is characterized by periodic discharges (PD), spike‐and‐waves or sharp‐and‐waves (SW), or lateralized rhythmic ...
Pilar Bosque‐Varela, Lukas Machegger, Wanda Lauth, Panagiota Eleni Tsalouchidou, Susanne Knake, Georg Zimmermann, Nicolas Jannone‐Pedro, Giada Giovannini, Stefano Meletti, Adrian Ridski Harsono, Fabio Rossini, Markus Leitinger, Johannes Pfaff, Sándor Beniczky, Eugen Trinka, Giorgi Kuchukhidze   +15 more
wiley   +1 more source