Results 201 to 210 of about 234,090 (282)

Applying Machine Learning Methods to Laser Acceleration of Protons: Synthetic Data for Exploring the High Repetition Rate Regime

open access: yesContributions 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

Probability prediction of true‐triaxial compressive strength of intact rocks based on the improved PSO‐RVM model

open access: yesDeep 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

Data‐driven analysis of the spatial dependence of grouting efficiency during tunnel excavation

open access: yesDeep 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

Bayesian-optimized machine learning boosts actual evapotranspiration prediction in water-stressed agricultural regions of China. [PDF]

open access: yesSci Rep
Elbeltagi A   +8 more
europepmc   +1 more source

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

open access: yesDeep 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

Bayesian continual learning and forgetting in neural networks. [PDF]

open access: yesNat Commun
Bonnet D   +6 more
europepmc   +1 more source

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

open access: yesDeep 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

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