Results 91 to 100 of about 31,786 (276)

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

Partition theorems and the Chinese Remainder Theorem

open access: yesDiscrete Mathematics
The famous partition theorem of Euler states that partitions of $n$ into distinct parts are equinumerous with partitions of $n$ into odd parts. Another famous partition theorem due to MacMahon states that the number of partitions of $n$ with all parts repeated at least once equals the number of partitions of $n$ where all parts must be even or ...
openaire   +3 more sources

Random finite element analysis on ground subsidence caused by tunnel excavation in karst regions with spatial variable soil

open access: yesDeep Underground Science and Engineering, EarlyView.
This study investigates ground subsidence during tunnel excavation in karst areas, highlighting the combined effects of karst cave proximity, cave size, and soil spatial variability. Findings suggest that shorter cave distances and larger cave sizes increase subsidence variability, and a modified Peck formula is proposed for more accurate subsidence ...
Zhenghong Su   +4 more
wiley   +1 more source

Domain‐adapted driving scene understanding with uncertainty‐aware and diversified generative adversarial networks

open access: yesCAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Autonomous vehicles are required to operate in an uncertain environment. Recent advances in computational intelligence techniques make it possible to understand driving scenes in various environments by using a semantic segmentation neural network, which assigns a class label to each pixel.
Yining Hua   +4 more
wiley   +1 more source

Shock wave propagation characteristics of aluminum‐containing explosive in corrugated steel‐lined tunnel

open access: yesDeep Underground Science and Engineering, EarlyView.
Aluminum‐enhanced afterburning renders AE explosives more hazardous than conventional ones. Corrugated steel linings reduce far‐field AE blast overpressure by ~50% through wave reflection and dissipation. The developed model accurately predicts peak pressure (<10% error) and arrival time (<3% error), supporting protective design.
Zhen Wang   +5 more
wiley   +1 more source

Upper bound limit analysis of coral reef limestone cavern roof stability incorporating a tension‐shear failure mechanism with tensile‐strength cut‐off

open access: yesDeep Underground Science and Engineering, EarlyView.
For the roof of coral reef limestone caverns, a novel tension‐shear composite failure mechanism was developed. The most critical tensile crack model was identified using a hybrid optimization algorithm, and the stability of the cavern roof was analyzed accordingly.
Dongsheng Xu, Chenxu Li, Chuantan Hou
wiley   +1 more source

Evaluation of the Adequacy of Design Specifications for Nonstructural Components in a Reticular Structure

open access: yesEarthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Nonstructural components (NSCs) installed in large‐span reticular structures were frequently severely damaged during earthquakes, even when the primary structure remained intact. Existing seismic design specifications for NSCs were predominantly developed for upright structures such as multi‐storey buildings and offer no guidance for reticular
Xudong Zhi   +6 more
wiley   +1 more source

Machine Learning Approaches to Forecast the Realized Volatility of Crude Oil Prices

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT This paper presents an evaluation of the accuracy of machine learning (ML) techniques in forecasting the realized volatility of West Texas Intermediate (WTI) crude oil prices. We compare several ML algorithms, including regularization, regression trees, random forests, and neural networks, to several heterogeneous autoregressive (HAR) models ...
Talha Omer   +3 more
wiley   +1 more source

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