Results 71 to 80 of about 8,190 (293)
Feature selection for probabilistic load forecasting via sparse penalized quantile regression
Journal of Modern Power Systems and Clean Energy, 2019 Probabilistic load forecasting (PLF) is able to present the uncertainty information of the future loads. It is the basis of stochastic power system planning and operation. Recent works on PLF mainly focus on how to develop and combine forecasting models,
Yi Wang +4 more
doaj +1 more source
Low-Dose CT Image Reconstruction With a Deep Learning Prior
IEEE Access, 2020 In low-dose computed tomography (LDCT), a penalized weighted least squares (PWLS) approach that incorporates the Poisson statistics of X-ray photons can significantly reduce excessive quantum noise.
Hyoung Suk Park +2 more
doaj +1 more source
Optimum smoothing parameter selection for penalized least squares in form of linear mixed effect models [PDF]
, 2012 24th Mini-EURO Conference on Continuous Optimization and Information-Based Technologies in the Financial Sector -- JUN 23-26, 2010 -- Izmir Univ Econom, Izmir, TURKEYWOS: 000304274600008In this article, we discuss the penalized least squares problem ...
Dursun Aydın +5 more
core +1 more source
Advanced Materials, EarlyView.We introduce a computational workflow that combines quantum chemical calculations and machine learning techniques to predict the catalytic performance of a wide range of catalysts in the nitrogen reduction reaction (NRR). The analysis of the trained models provides insights into the complex structure–activity relationship in experimental catalytic ...
Leonardo Di Ciano +5 more
wiley +1 more source
Derivative-free optimization and neural networks for robust regression [PDF]
, 2012 Large outliers break down linear and nonlinear regression models. Robust regression methods allow one to filter out the outliers when building a model.
Kelarev, Andrei +2 more
core +2 more sources
Advanced Materials, EarlyView.A deep learning inverse‐design framework is established to create versatile reconfigurable terahertz metadevices. By synergizing deep learning with phase‐change materials, this approach enables on‐demand customization of multidimensional electromagnetic responses.
Yisheng Dong +11 more
wiley +1 more source
International Journal of Biomedical Imaging, 2007 Conjugate gradient method is verified to be efficient for nonlinear optimization problems of large-dimension data. In this paper, a penalized linear and nonlinear combined conjugate gradient method for the reconstruction of fluorescence molecular ...
Shang Shang +4 more
doaj +1 more source
On the properties of the solution path of the constrained and penalized L2-L0 problems [PDF]
, 2009 12 pagesTechnical report on the properties of the L0-constrained least-square minimization problem and the L0-penalized least-square minimization problem: domain of optimization, notion of solution path, properties of the "penalized" solution path..
Soussen, Charles +3 more
core +3 more sources
A Rank-Deficient and Sparse Penalized Optimization Model for Compressive Indoor Radar Target Localization [PDF]
, 2020 This paper proposes a rank-deficient and sparse penalized optimization method for addressing the problem of through-wall radar imaging (TWRI) in the presence of structured wall clutter.
Nguyen, Van-Giang, Tang, Van Ha
core +2 more sources
Advanced Materials Interfaces, EarlyView.An intentionally added, chemically formed LixAlSy coating stabilizes the lithium–electrolyte interface in solid‐state Li–S batteries. The layer suppresses side reactions, preserves smooth charge transfer, and improves ion transport from the start. This approach offers a practical route to more durable solid‐state batteries and a clearer understanding ...
Xinyi Wang +4 more
wiley +1 more source