Results 61 to 70 of about 7,354 (203)

Coal and Gas Outburst Behavior in Gas‐Bearing Tunnels Revealed Through an Interpretable ISSA‐DNN Learning Framework

open access: yesGeofluids, Volume 2026, Issue 1, 2026.
Coal and gas outbursts represent one of the most severe safety hazards during the construction of gas‐bearing tunnels. Accurate risk prediction remains difficult because of complex geological conditions, limited sample sizes, and the inherent subjectivity in hazard classification.
Fangyin Wu   +6 more
wiley   +1 more source

Fair Kernel Learning

open access: yes, 2017
New social and economic activities massively exploit big data and machine learning algorithms to do inference on people's lives. Applications include automatic curricula evaluation, wage determination, and risk assessment for credits and loans. Recently,
Camps-Valls, Gustau   +5 more
core   +1 more source

Determining the Particle Size of Pulverized Coal From Spectral Reflectivity Measurements

open access: yesJournal of Spectroscopy, Volume 2026, Issue 1, 2026.
Pulverized coal is widely used in industrial energy supplies and chemical production. Its combustion efficiency and reactivity are closely related to its particle size distribution. Therefore, precise, fast, and reliable measurement methods are required to determine the particle size of pulverized coal.
Chengkun Wang   +6 more
wiley   +1 more source

A Novel Method on Recognizing Drum Load of Elastic Tooth Drum Pepper Harvester Based on CEEMDAN-KPCA-SVM

open access: yesAgriculture
The operational complexities of the elastic tooth drum pepper harvester (ETDPH), characterized by variable drum loads that are challenging to recognize due to varying pepper densities, significantly impact pepper loss rates and mechanical damage.
Xinyu Zhang   +5 more
doaj   +1 more source

Fault condition recognition of rolling bearing in bridge crane based on PSO–KPCA

open access: yesMATEC Web of Conferences, 2017
When the rolling bearing in bridge crane gets out of order and often accompanies with occurrence of nonlinear behaviours, its fault information is weak and it is difficult to extract fault features and to distinguish diverse failure modes.
He Yan, Wang Zongyan
doaj   +1 more source

Stratified Transfer Learning for Cross-domain Activity Recognition

open access: yes, 2017
In activity recognition, it is often expensive and time-consuming to acquire sufficient activity labels. To solve this problem, transfer learning leverages the labeled samples from the source domain to annotate the target domain which has few or none ...
Chen, Yiqiang   +4 more
core   +1 more source

Enhancing Wind Turbine Diagnostics With SCADA‐Vibration Fusion, Contrastive Learning, and Linear Predictive Coefficients

open access: yesStructural Control and Health Monitoring, Volume 2026, Issue 1, 2026.
Wind energy plays a pivotal role in the transition to sustainable power generation. However, maintaining the reliability and efficiency of wind turbine (WT) remains a significant challenge due to complex operational conditions and the high cost associated with unexpected failures.
Cristian Velandia-Cárdenas   +3 more
wiley   +1 more source

Machine learning‐based research of new refractory high‐entropy alloys using guided multiobjectives search strategy

open access: yesMaterials Genome Engineering Advances, Volume 3, Issue 4, December 2025.
This study introduces an integrated machine learning framework combining predictive models, a guided multiobjective search strategy, and particle swarm optimization (PSO) to discover novel refractory high‐entropy alloys with exceptional yield strengths (1580–1740 MPa) and fracture strains (23%–27%), overcoming challenges of vast composition spaces and ...
Gang Xu   +6 more
wiley   +1 more source

Projection‐based estimators for matrix/tensor‐valued data

open access: yesScandinavian Journal of Statistics, Volume 52, Issue 4, Page 2152-2186, December 2025.
Abstract A general approach for extending estimators to matrix‐ and tensor‐valued data is proposed. The extension is based on using random projections to project out dimensions of a tensor and then computing a multivariate estimator for each projection. The mean of the obtained set of estimates is used as the final, joint estimate. In some basic cases,
Joni Virta   +2 more
wiley   +1 more source

RECOGNITION METHOD OF METAL FRACTURE IMAGES BASED ON GROUPLET TRANSFORM AND KERNEL PRINCIPAL COMPONENT ANALYSIS

open access: yesJixie qiangdu, 2016
Grouplet transform is a new directional wavelet. This wavelet can be transformed at any time and space,and adaptively change the basis according to image texture.
LI ZhiNong   +3 more
doaj  

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