Contributions to Plasma Physics, EarlyView.ABSTRACT Advances in ultra‐intense laser technology have increased repetition rates and average power for chirped‐pulse laser systems, which offer a promising solution for many applications including energetic proton sources. An important challenge is the need to optimize and control the proton source by varying some of the many degrees of freedom ...
John J. Felice +7 more
wiley +1 more source
Deep Underground Science and Engineering, EarlyView.In this work, we propose an improved particle swarm optimization (PSO) algorithm and develop an improved PSO‐relevance vector machine (RVM) model as a substitute for traditional true‐triaxial testing. The model's high prediction accuracy was validated through comparisons with two other machine learning methods and five three‐dimensional Hoek–Brown type
Qi Zhang +4 more
wiley +1 more source
Bio-RegNet: A Meta-Homeostatic Bayesian Neural Network Framework Integrating Treg-Inspired Immunoregulation and Autophagic Optimization for Adaptive Community Detection and Stable Intelligence. [PDF]
Biomimetics (Basel)Ma Y, Qu D, Pyrozhenko M.
europepmc +1 more source
Data‐driven analysis of the spatial dependence of grouting efficiency during tunnel excavation
Deep Underground Science and Engineering, EarlyView.Prediction of grouting efficiency using machine learning is enhanced by adopting a training strategy that accounts for the grouting process across multiple rounds. Abstract Grouting with water–cement mixtures is the most widely used and cost‐effective method for managing excess water inflow during tunnel construction.
Huaxin Liu, Xunchang Fei, Wei Wu
wiley +1 more source
Distinguishing Between Healthy and Unhealthy Newborns Based on Acoustic Features and Deep Learning Neural Networks Tuned by Bayesian Optimization and Random Search Algorithm. [PDF]
Entropy (Basel)Lahmiri S, Tadj C, Gargour C.
europepmc +1 more source
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 +4 more
wiley +1 more source
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 +4 more
wiley +1 more source
Optimizing Image Segmentation for Microstructure Analysis of High-Strength Steel: Histogram-Based Recognition of Martensite and Bainite. [PDF]
Materials (Basel)Hallo F +4 more
europepmc +1 more source
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 +6 more
wiley +1 more source
Two-Tier heuristic search for ransomware-as-a-service based cyberattack défense analysis using explainable Bayesian deep learning model. [PDF]
Sci RepAlmuflih AS.
europepmc +1 more source