Zobrazeno 1 - 10
of 345
pro vyhledávání: '"sparse identification"'
Publikováno v:
Shanghai Jiaotong Daxue xuebao, Vol 58, Iss 11, Pp 1753-1761 (2024)
This paper addresses the issue of perching maneuver of unmanned aerial vehicles in wind-disturbed environments, by combining the control-oriented sparse identification of nonlinear dynamics with control (SINDYc) method and the imitation deep reinforc
Externí odkaz:
https://doaj.org/article/c57db7ef5cb442baa49d35e29977f5d3
Publikováno v:
Frontiers in Energy Research, Vol 12 (2024)
In the field of renewable energy, accurate long-term time series forecasting is crucial for optimizing the operation of power systems and reducing risks. Due to the intermittency of renewable energy sources, traditional data-driven deep learning meth
Externí odkaz:
https://doaj.org/article/bf658a6574e8495983069baaeaaf2ea5
Publikováno v:
Water Research X, Vol 25, Iss , Pp 100276- (2024)
Real-time monitoring of key quality variables is essential and crucial for stable and safe operations of wastewater treatment plants (WWTPs). Next generation reservoir computing (NG-RC) has recently garnered significant attention in quality predictio
Externí odkaz:
https://doaj.org/article/110ac9e911dd4e8ab341124344c7219c
Publikováno v:
Royal Society Open Science, Vol 11, Iss 10 (2024)
Reduced-order models (ROMs) have been widely adopted in fluid mechanics, particularly in the context of Newtonian fluid flows. These models offer the ability to predict complex dynamics, such as instabilities and oscillations, at a considerably reduc
Externí odkaz:
https://doaj.org/article/bfd157fdb0e74bd18631b51bd6053d38
Publikováno v:
Results in Engineering, Vol 23, Iss , Pp 102389- (2024)
Structural Health Monitoring (SHM) techniques are key to monitor the health state of engineering structures, where damage type, location and severity are to be estimated by applying sophisticated techniques to signals measured by sensors. However, ve
Externí odkaz:
https://doaj.org/article/51c3845f354b4adbb07e7dcb33c1543a
Autor:
Jinho Choi
Publikováno v:
IEEE Open Journal of Signal Processing, Vol 5, Pp 1107-1118 (2024)
In order to extract governing equations from time-series data, various approaches are proposed. Among those, sparse identification of nonlinear dynamics (SINDy) stands out as a successful method capable of modeling governing equations with a minimal
Externí odkaz:
https://doaj.org/article/ebf47673900f49da990956f756a19abc
Publikováno v:
IEEE Access, Vol 12, Pp 169592-169605 (2024)
The dynamic model equations are essential in system analysis and control system design. In adaptive control systems, the mathematical equations of the controlled system are utilized to compute the corresponding control signals based on the current dy
Externí odkaz:
https://doaj.org/article/4190f1e004ee43c09cc01c0cc67985c3
Publikováno v:
IEEE Access, Vol 12, Pp 119272-119291 (2024)
This paper presents a novel physics-based data-driven approach for reconstructing the nonlinear governing equations and suppressing vibrations in vertical-shaft rotary machines during transient motion. We first identify the key nonlinear terms using
Externí odkaz:
https://doaj.org/article/63cee3790705425899bd333825e0a6b1
Publikováno v:
In Journal of Wind Engineering & Industrial Aerodynamics July 2024 250
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