An optimal Bayesian regularization for force reconstruction problems
Sign Up to like & getrecommendations! Published in 2019 at "Mechanical Systems and Signal Processing"
DOI: 10.1016/j.ymssp.2019.02.021
Abstract: In a paper, recently published in Mechanical Systems and Signal Processing, we have proposed a full Bayesian inference for reconstructing mechanical sources acting on a linear and time invariant structure. The main interest of this… read more here.
Keywords: optimal bayesian; reconstruction problems; regularization; force reconstruction ... See more keywords
Bayesian regularization of multilayer perceptron neural network for estimation of mass attenuation coefficient of gamma radiation in comparison with different supervised model-free methods
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Instrumentation"
DOI: 10.1088/1748-0221/15/11/p11019
Abstract: Multilayer perceptron (MLP) neural networks have been used extensively for estimation/regression of parameters. Moreover, recent studies have shown that learning algorithms of MLP which are based on Gaussian function are more accurate. In this paper,… read more here.
Keywords: multilayer perceptron; attenuation coefficient; regularization; mass attenuation ... See more keywords
Prediction of GPS-TEC on Mw > 5 Earthquake Days Using Bayesian Regularization Backpropagation Algorithm
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2023.3262028
Abstract: The detection of earthquake precursor signals a few days before the earthquake day is one of the most studied subjects today. In recent years, a strong correlation is observed between earthquakes and ionospheric parameters. In… read more here.
Keywords: bayesian regularization; earthquake days; algorithm; tec earthquake ... See more keywords