Results 141 to 150 of about 98,314 (264)
Retraction: Cerebral microbleed detection via convolutional neural network and extreme learning machine. [PDF]
Frontiers Editorial Office.
europepmc +1 more source
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen +7 more
wiley +1 more source
A novel hybrid extreme learning machine-based diagnosis model for sensor node faults in aquaculture. [PDF]
Shi B, Gao Z, Pu T, Jiang J, Sun Y.
europepmc +1 more source
A foldable bimodal sensor integrates a triboelectric nanogenerator and graphene piezoresistive effect into a monolithic laser‐induced graphene film. It enables synchronous non‐contact and tactile perception, achieving a distance of 110 mm, a sensitivity of 11.2 kPa−1, and a response time of 10 ms.
Weixiong Yang +10 more
wiley +1 more source
Complex Environmental Geomagnetic Matching-Assisted Navigation Algorithm Based on Improved Extreme Learning Machine. [PDF]
Huang J, Hu Z, Yi W.
europepmc +1 more source
This work proposes and constructs the Hefei‐NAMD‐S framework based on machine learning stacked models to investigate the relationship between local polarization and non‐radiative recombination. The results indicate that, compared with A‐site local polarization, B‐site local polarization shows a more evident association with the non‐radiative ...
Bing Yang +13 more
wiley +1 more source
Prediction of Thermomechanical Behavior of Wood-Plastic Composites Using Machine Learning Models: Emphasis on Extreme Learning Machine. [PDF]
Hua X +6 more
europepmc +1 more source
Entropy Decoding the Fundamental Law of Phase Competition in Glass Formation
We validate the integration of intermetallic and eutectic phases as initial phases for composition design. The phase competition mechanism in glass formation is quantitatively clarified based on the melting entropy of competing phases. Glass‐forming ability is modulated by tuning phase competition via the melting entropy of initial phases.
Benke Huo +7 more
wiley +1 more source
Mechanistic Understanding of Protein–MOF Integration Through Surfactant‐Driven Interfacial Design
This study reveals how surfactant‐driven interfacial design governs the assembly and stability of protein@MOF composites. Using lipid‐based nonionic surfactants, we modulate protein–MOF interactions to improve encapsulation efficiency, MOF crystallization, and catalytic performance.
Ehsan Rashidniyaghi +4 more
wiley +1 more source
Traffic flow prediction based on improved deep extreme learning machine. [PDF]
Tian X +5 more
europepmc +1 more source

