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Toplam kayıt 7, listelenen: 1-7
Early detection of rogue waves using compressive sampling
(Işık University Press, 2019)
We discuss the possible usage of the compressive sampling for the early detection of the rogue waves. One of the promising techniques for the early detection of the rogue waves is to measure the triangular Fourier spectra ...
Effects of ground water table and ground inclination on train induced ground-borne vibrations
(Işık University Press, 2019)
Passage of the train wheels induces ground-borne vibrations at the railwheel interface, where the main contribution is due to the axle loads moving on irregular track and wheel interface. These vibrations can cause problems ...
A tomographic approach for the early detection of 2D rogue waves
(Işık University Press, 2020-01-23)
In this paper we propose an efficient tomographic approach for the early detection of 2D rogue waves. The method relies on the principle of detecting conical spectral features before rogue wave becomes evident in time. ...
A split-step Fourier scheme for the dissipative Kundu-Eckhaus equation and its rogue wave dynamics
(Işık University Press, 2021-01)
We investigate the rogue wave dynamics of the dissipative Kundu-Eckhaus equation. With this motivation, we propose a split-step Fourier scheme for its numerical solution. After testing the accuracy and stability of the ...
Efficient sensing of ground-borne vibrations induced by pile driving using compressive sampling
(Işık University Press, 2022)
In this paper, we propose and discuss the applicability of the compressive sensing (CS) for the measurement and analysis of the ground-borne vibrations induced by pile driving. With this motivation, we consider two types ...
Self-localized soliton solutions of the nonlinear quantum harmonic oscillator
(Işık University Press, 2022)
We analyze the existences, properties and stabilities of the self-localized solutions of the nonlinear quantum harmonic oscillator (NQHO) using spectral renormalization method (SRM). We show that self-localized single and ...
Predicting the ocean currents using deep learning
(Işık University Press, 2023-01)
In this paper, we analyze the predictability of the ocean currents using deep learning. More specifically, we apply the Long Short Term Memory (LSTM) deep learning network to a data set collected by the National Oceanic ...