Results 71 to 80 of about 62,392 (177)
Computational and Machine‐Learning Studies of Ethylene Oligomerization
This review focuses on recent advances in computational and machine‐learning studies of ethylene oligomerization, highlighting mainstream catalyst systems based on Co, Ta, Ti, Zr, and Hf, with particular emphasis on Fe‐ and Cr‐based catalysts and their controlling factors governing reactivity and LAO distribution.
Zhixin Qin +3 more
wiley +1 more source
Periodic orbits around areostationary points in the Martian gravity field
This study investigates the problem of areostationary orbits around Mars in the three-dimensional space. Areostationary orbits are expected to be used to establish a future telecommunication network for the exploration of Mars.
Baoyin, Hexi, Liu, Xiaodong, Ma, Xingrui
core +1 more source
Data‐driven analysis of the spatial dependence of grouting efficiency during tunnel excavation
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
The objective of this research is to establish the modelling and evaluation of a differential mathematical system for the radiated Carreau nanofluid model (RCNFM) by exploiting the skills of stochastic computing with Levenberg–Marquardt neural networks ...
Zahoor Shah +9 more
doaj +1 more source
Optimized Dual ANN Control Technique for Efficient Energy Management System (EMS) of Microgrid
Proposed methodology. ABSTRACT The escalating global energy demand necessitates a shift towards sustainable and environmentally friendly alternatives. While renewable energy sources like solar and wind energy offer promising solutions, their intermittent nature poses significant challenges for grid integration.
Bin Li +5 more
wiley +1 more source
Levenberg-Marquardt backpropagation has emerged as a powerful method in the field of heat transfer, despite its original use in the training of artificial neural networks.
Nidhi N. Pai +3 more
doaj +1 more source
Implementation and testing of selected optimization methods for the parameter estimation of simulation models [PDF]
Tato práce se zabývá návrhem vhodných optimalizačních algoritmů pro potřeby nově vyvíjeného nástroje Mechlab’s parameter estimation, který slouží pro odhad parametrů simulačních modelů v prostředí Matlab/Simulink.
Zapletal, Marek
core
A trade‐off between efficiency and stability in a class of sky‐blue organic light‐emitting diodes
OLED efficiency and stability are correlated with device structure using combined experimental and simulation approach. Efficient, but less stable devices suffer mainly from exciton‐exciton annihilation, while their opposites have excitons predominantly quenched by polarons.
Eglė Tankelevičiūtė +4 more
wiley +1 more source
The handheld Raman with SSE system efficiently mitigates fluorescence; however, it may also bias the Raman response towards graphitic domains in carbon‐based black pigments, thereby concealing amorphous carbon contributions that are critical for pigment type identification.
Zeynep Alp, Christoph Herm
wiley +1 more source
Neural network training acceleration using NVIDIA CUDA technology for image recognition
In this paper, an implementation of neural network trained by algorithm based on Levenberg-Marquardt method is presented. Training of neural network increased by almost 9 times using NVIDIA CUDA technology.
Alexander A Fertsev
doaj +3 more sources

