Results 91 to 100 of about 4,101,445 (240)
Energy Reports, 2020 Environmental noise is a key factor affecting the quality of life in modern societies as they influence an extended set of human activities. Unwanted sounds, typically characterized as noise, can be of many types and vary in their impact and the ways to ...
Eleni Tsalera +2 more
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, 2014 In this paper we present a unified framework for solving a general class of problems arising in the context of set-membership estimation/identification theory.
Cerone, Vito +3 more
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International Journal of Mechanical System Dynamics, EarlyView.ABSTRACT Geometrically nonlinear static analysis of materially imperfect composite doubly curved shells is investigated via the generalised differential quadrature method. The effects of both shear and thickness deformation are considered through a thickness‐ and shear‐deformable third‐order theory formulated in curvilinear coordinates, while the ...
Behrouz Karami +3 more
wiley +1 more source
Multisensor Estimation Fusion with Gaussian Process for Nonlinear Dynamic Systems
Entropy, 2019 The Gaussian process is gaining increasing importance in different areas such as signal processing, machine learning, robotics, control and aerospace and electronic systems, since it can represent unknown system functions by posterior probability.
Yiwei Liao +3 more
doaj +1 more source
On Chebyshev centers in metric spaces
Publications de l'Institut Mathematique, 2019 A Chebyshev center of a set A in a metric space (X,d) is a point of X best approximating the set A i.e., it is a point x0 ? X such that supy?A d(x0,y) = infx?X supy?A d(x,y). We discuss the existence and uniqueness of such points in metric spaces thereby generalizing and extending several known result on the subject.
openaire +3 more sources
, 2005 Inspiraling compact binaries are promising sources of gravitational waves for ground and space-based laser interferometric detectors. The time-dependent signature of these sources in the detectors is a well-characterized function of a relatively small ...
C. E. Shannon +8 more
core +1 more source
Elastoplasticity Informed Kolmogorov–Arnold Networks Using Chebyshev Polynomials
International Journal for Numerical and Analytical Methods in Geomechanics, EarlyView.ABSTRACT Multilayer perceptron (MLP) networks are predominantly used to develop data‐driven constitutive models for granular materials. They offer a compelling alternative to traditional physics‐based constitutive models in predicting non‐linear responses of these materials, for example, elastoplasticity, under various loading conditions. To attain the
Farinaz Mostajeran, Salah A. Faroughi
wiley +1 more source
Wildlife Biology, EarlyView.Exploration of new wildlife surveying methodologies that leverage advances in sensor technology and machine learning has led to tentative research into the application of seismology techniques. This, most commonly, involves the deployment of a footfall trap – a seismic sensor and data logger customised for wildlife footfall.
Benjamin J. Blackledge +4 more
wiley +1 more source
CAAI Transactions on Intelligence Technology, EarlyView.Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma +4 more
wiley +1 more source
A Dynamic Correlation‐Information‐Fusion‐Based Spatiotemporal Network for Traffic Flow Forecasting
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Traffic Flow Forecasting (TFF) is a foundational task in the development of Intelligent Transport Systems (ITSs). The primary challenge is to undertake a comprehensive exploration of the intrinsic dynamic spatiotemporal correlations of the road network, unveiling the long‐term evolutionary traffic trends.
Dawen Xia +6 more
wiley +1 more source