Results 91 to 100 of about 1,952 (235)

Modeling rainfall drop size distribution moments using an S‐band polarimetric radar in complex terrain

open access: yesQuarterly Journal of the Royal Meteorological Society, EarlyView.
Using S‐band dual‐polarization radar and disdrometers during PRECIP 2022 in Taiwan, we analyze a Mei‐Yu frontal event with widespread stratiform rain and embedded convection. Multiple disdrometers are used to create a novel drop size distribution model for S‐band radars resolving both the drizzle and precipitation modes. The model reveals both inferred
Ian C. Cornejo   +3 more
wiley   +1 more source

On the asymptotic behaviour of deterministic and stochastic volterra integro-differential equations [PDF]

open access: yes, 2007
This thesis examines a question of stability in stochastic and deterministic systems with memory, and involves studying the asymptotic properties of Volterra integro-differential equations.
Devin, Siobhan
core  

Crosstalk Statistics via Collocation Method [PDF]

open access: yes, 2009
A probabilistic model for the evaluation of transmission lines crosstalk is proposed. The geometrical parameters are assumed to be unknown and the exact solution is decomposed into two functions, one depending solely on the random parameters and the ...
Diouf, F.   +5 more
core   +1 more source

Control Systems Design With Enlarged Stability Domains for Nonlinear Constrained Systems via Sum‐of‐Squares Optimization

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Designing safe control laws for nonlinear systems is challenging, especially when ensuring stability under actuator saturation and state constraints. A key aspect is embedding controllers with a Region of Attraction (ROA), which defines initial conditions guaranteeing convergence to a stable equilibrium point (EP).
Bhaskar Biswas   +3 more
wiley   +1 more source

A Sparse Stochastic Collocation Technique for High-Frequency Wave Propagation with Uncertainty [PDF]

open access: yes, 2016
We consider the wave equation with highly oscillatory initial data, where there is uncertainty in the wave speed, initial phase, and/or initial amplitude.
Tempone, R.   +6 more
core   +1 more source

Stochastic Bias Correction and Uncertainty Estimation of Satellite-Retrieved Soil Moisture Products

open access: yesRemote Sensing, 2017
To apply satellite-retrieved soil moisture to a short-range weather prediction, we review a stochastic approach for reducing foot print scale biases and estimating its uncertainties. First, we discuss a challenge of representativeness errors.
Ju Hyoung Lee, Chuanfeng Zhao, Yann Kerr
doaj   +1 more source

Model‐Based Systems Engineering in Space Applications: A Comprehensive Literature Review

open access: yesSystems Engineering, EarlyView.
ABSTRACT The growing complexity of space engineering is driving the demand to embrace the adoption of Model‐Based Systems Engineering (MBSE). Although the MBSE is well‐practiced in the space industry, the level of effort and need required to obtain the benefits of MBSE vastly differ across enterprises; this disparity presents a significant challenge to
Rehobot Bekele Buruso   +4 more
wiley   +1 more source

A novel solution for stochastic dynamic game of water allocation from a reservoir using collocation method [PDF]

open access: yes, 2011
In this study, a continuous model of stochastic dynamic game for water allocation from a reservoir system was developed. The continuous random variable of inflow in the state transition function was replaced with a discrete approximant rather than using ...
Ganji, Arman   +5 more
core   +1 more source

An Efficient Deterministic-Stochastic Model of the Human Body Exposed to ELF Electric Field

open access: yesInternational Journal of Antennas and Propagation, 2016
The paper deals with the deterministic-stochastic model of the human body represented as cylindrical antenna illuminated by a low frequency electric field.
Anna Šušnjara, Dragan Poljak
doaj   +1 more source

A Detailed and Comprehensive Account of Fractional Physics‐Informed Neural Networks: From Implementation to Efficiency

open access: yesArtificial Intelligence for Engineering, EarlyView.
Caputo‐based fPINNs accurately solve fractional ODEs and PDEs while exposing an accuracy–cost trade‐off driven by the history‐dependent fractional derivative. Temporal collocation and shorter time windows are the most effective strategies for improving early‐time accuracy without unnecessary spatial refinement.
Donya Dabiri   +4 more
wiley   +1 more source

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