Results 21 to 30 of about 3,497,223 (309)

Transient stability analysis of one special type of AC microgrids with a gas reciprocating generator unit

open access: yesThe Journal of Engineering, 2019
More and more gas reciprocating generator units are integrated into offshore platforms, due to their compact structure and high efficiency. This paper concentrates on the transient stability analysis of one special type of AC microgrids containing a gas ...
Liu Jun   +5 more
doaj   +1 more source

Analytical modelling of a slotless tubular interior permanent magnet machine considering iron poles permeability

open access: yesIET Electric Power Applications, 2023
An analytical method is proposed to model the magnetic field distribution across a slotless tubular interior permanent magnet machine. In order to consider the permeability of both permanent magnets and iron poles of the slider, in the proposed approach,
Mohammad Hosein Javanmardi   +1 more
doaj   +1 more source

A method to measure the damping introduced by linear guides in large milling machines

open access: yes, 2022
Publisher Copyright: © 2022Simulation of the dynamic behavior of a milling machine requires accurate stiffness, inertia, and damping values. Unlike the properties of stiffness and inertia, damping values are not generally available in the bibliography ...
Oleaga, I.   +3 more
core   +1 more source

Comparative Study of Linear Variable Flux Reluctance Machine with Linear Wound Field Flux Reversal Machine

open access: yesCES Transactions on Electrical Machines and Systems, 2023
As members of doubly salient magnetless linear machines, linear variable flux reluctance (LVFR) and wound field flux reversal (LWFFR) machines inherit the merits of conventional magnetless linear machines such as low cost, high flux adjustment capability
Tingting Jiang   +3 more
doaj   +1 more source

Machine Learning for Semi Linear PDEs [PDF]

open access: yesJournal of Scientific Computing, 2019
Recent machine learning algorithms dedicated to solving semi-linear PDEs are improved by using different neural network architectures and different parameterizations. These algorithms are compared to a new one that solves a fixed point problem by using deep learning techniques.
Quentin Chan-Wai-Nam   +2 more
openaire   +3 more sources

The complexity of small universal Turing machines : a survey [PDF]

open access: yes, 2009
We survey some work concerned with small universal Turing machines, cellular automata, tag systems, and other simple models of computation. For example it has been an open question for some time as to whether the smallest known universal Turing machines ...
Woods, Damien, Neary, Turlough
core   +1 more source

Nomograms for Visualizing Linear Support Vector Machines [PDF]

open access: yes, 2004
Support vector machines are often considered to be black box learning algorithms. We show that for linear kernels it is possible to open this box and visually depict the content of the SVM classifier in high-dimensional space in the interactive format of
Ivan Bratko   +9 more
core   +2 more sources

Power flow in the air gap of linear electrical machines by utilization of the Poynting vector: Part 1 ‐ Analytical expressions

open access: yesThe Journal of Engineering, 2022
Analytical solutions and estimations for the power flow in the air gap of linear electrical machines of different geometries are derived from Poynting's theorem.
Anna E. Frost   +3 more
doaj   +1 more source

Development of low translator mass linear Vernier machine for wave energy power take off

open access: yesThe Journal of Engineering, 2019
This article proposes a new topology of double-sided linear Vernier permanent magnet (LVPM) machine with segmented translator structure. A combination of a typical Halbach array consists of two horizontally magnetised permanent magnets (PMs) sandwiched ...
Mohammad A.H. Raihan   +3 more
doaj   +1 more source

Support Vector Machines for Predicting Electrical Faults [PDF]

open access: yesEngineering and Technology Journal, 2014
Support vector machines (SVMs) are a non-probabilistic binary linear classifier in machine learning techniques and are supervised learning algorithms that classify, predict, recognise and analyse patterns.
Tarik Rashid, Salar J. Abdulhameed
doaj   +1 more source

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