2018
DOI: 10.2298/tsci1804823d
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Spatio-temporal dynamics and interaction of lump solutions for the (4+1)-D Fokas equation

Abstract: The (4+1)-D Fokas equation is a new and important physical model. Its Hirota's bilinear form with a perturbation parameter is obtained by an appropriate transformation. A class of lump solutions and three different forms of spatio-temporal structure are obtained. Meanwhile, the theoretical analysis for the change of spatio-temporal structure is discussed by using the extreme value theory of multivariate function. Finally, the interaction between a stripe soliton and lump solution is discussed, and a new wave p… Show more

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Cited by 4 publications
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“…The burgeoning demand for real-time performance has become a critical requirement for many scientific, industrial, and commercial applications, such as computational biology, weather forecasting, autonomous vehicles, and financial analytics. This requirement is largely driven by the rapid progress in computer technology, including advances in hardware and software, which have enabled the processing of vast quantities of data in real-time Dai et al, 2018;Tan, 2021;. Real-time performance is essential for many time-sensitive applications, where delays or inaccuracies in processing can have severe consequences, such as in real-time monitoring of critical physiological signals or detecting anomalies in sensor data.…”
Section: Neural Network Model With Non-linear Afmentioning
confidence: 99%
“…The burgeoning demand for real-time performance has become a critical requirement for many scientific, industrial, and commercial applications, such as computational biology, weather forecasting, autonomous vehicles, and financial analytics. This requirement is largely driven by the rapid progress in computer technology, including advances in hardware and software, which have enabled the processing of vast quantities of data in real-time Dai et al, 2018;Tan, 2021;. Real-time performance is essential for many time-sensitive applications, where delays or inaccuracies in processing can have severe consequences, such as in real-time monitoring of critical physiological signals or detecting anomalies in sensor data.…”
Section: Neural Network Model With Non-linear Afmentioning
confidence: 99%