The wavelet scaling approach to forecasting: Verification on a large set of Noisy data
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Forecasting"
DOI: 10.1002/for.2634
Abstract: In the paper, we undertake a detailed empirical verification of wavelet scaling as a forecasting method through its application to a large set of noisy data. The method consists of two steps. In the first,… read more here.
Keywords: set noisy; noisy data; wavelet scaling; large set ... See more keywords
Multiquadric trigonometric spline quasi-interpolation for numerical differentiation of noisy data: a stochastic perspective
Sign Up to like & getrecommendations! Published in 2017 at "Numerical Algorithms"
DOI: 10.1007/s11075-017-0313-1
Abstract: Based on multiquadric trigonometric spline quasi-interpolation, the paper proposes a scheme for numerical differentiation of noisy data, which is a well-known ill-posed problem in practical applications. In addition, in the perspective of kernel regression, the… read more here.
Keywords: differentiation noisy; noisy data; multiquadric trigonometric; numerical differentiation ... See more keywords
A Machine Learning Approach for Structural Health Monitoring Using Noisy Data Sets
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Automation Science and Engineering"
DOI: 10.1109/tase.2019.2950958
Abstract: Continuous structural health monitoring of civil infrastructure can be achieved by deploying an Internet of Things network of distributed acceleration sensors in buildings to capture floor movement. Postdisaster damage levels can be computed based on… read more here.
Keywords: health monitoring; structural health; machine; noisy data ... See more keywords