Results 61 to 70 of about 12,024 (199)
Sparse Volterra and Polynomial Regression Models: Recoverability and Estimation
, 2011 Volterra and polynomial regression models play a major role in nonlinear system identification and inference tasks. Exciting applications ranging from neuroscience to genome-wide association analysis build on these models with the additional requirement ...
Giannakis, Georgios B. +1 more
core +1 more source
Predicting solar cell efficiencies using historical data from a manufacturing process
The Canadian Journal of Chemical Engineering, EarlyView.Abstract The solar cell manufacturing data of a passivated emitter and rear cell solar cell manufacturing plant was studied to assess the effects of tool usage and the processing time spent on each tool on the solar cell efficiency. Since manufacturing processes involve several steps with multiple tools, tracing their quality parameters back to the ...
Sushmita Mittra, Vinay Prasad
wiley +1 more source
Energies, 2018 Thermal load and indoor comfort level are two important building performance indicators, rapid predictions of which can help significantly reduce the computation time during design optimization. In this paper, a three-step approach is used to develop and
Yaolin Lin +4 more
doaj +1 more source
Wastewater Quality Estimation through Spectrophotometry-Based Statistical Models
Sensors, 2020 Local administrations are increasingly demanding real-time continuous monitoring of pollution in the sanitation system to improve and optimize its operation, to comply with EU environmental policies and to reach European Green Deal targets.
Daniel Carreres-Prieto +3 more
doaj +1 more source
Adaptive Higher-order Spectral Estimators
, 2017 Many applications involve estimation of a signal matrix from a noisy data matrix. In such cases, it has been observed that estimators that shrink or truncate the singular values of the data matrix perform well when the signal matrix has approximately low
Gerard, David, Hoff, Peter
core +1 more source
Journal of Chemical Technology &Biotechnology, EarlyView.Abstract BACKGROUND Selecting an optimal chromatography resin during biopharmaceutical downstream process development is a great challenge. This is especially the case for recombinant subunit vaccines, where product properties vary greatly and recovery often involves cell lysis, which yields a complex mixture of different host cell materials. Host cell
Tim Neijenhuis +4 more
wiley +1 more source
Predicting Slope Stability Failure through Machine Learning Paradigms
ISPRS International Journal of Geo-Information, 2019 In this study, we employed various machine learning-based techniques in predicting factor of safety against slope failures. Different regression methods namely, multi-layer perceptron (MLP), Gaussian process regression (GPR), multiple linear regression ...
Dieu Tien Bui +4 more
doaj +1 more source
Calibration and Validation of a Measurements-Independent Model for Road Traffic Noise Assessment
Applied Sciences, 2023 The assessment of road traffic noise is very important for the health of people living in urban areas. Noise is usually assessed by field measurements, and predictive models play an important role when experimental data are not available.
Domenico Rossi +2 more
doaj +1 more source
Parameter Estimation from an Optimal Projection in a Local Environment
, 2008 The parameter fit from a model grid is limited by our capability to reduce the number of models, taking into account the number of parameters and the non linear variation of the models with the parameters.
A. Bijaoui +3 more
core +1 more source
A literature survey of low-rank tensor approximation techniques [PDF]
, 2013 During the last years, low-rank tensor approximation has been established as a new tool in scientific computing to address large-scale linear and multilinear algebra problems, which would be intractable by classical techniques.
Grasedyck, Lars +2 more
core +1 more source