Results 131 to 140 of about 4,993,128 (318)

Optimization of the Production of Rubber Compounds Using Mathematical Models

Advanced Engineering Materials, EarlyView.
Rubber compounds were mixed in a batch internal mixer, and symbolic regression was used to derive mathematical models linking recipe and process parameters to ram path, torque, and mixing quality (incorporation, dispersion, distribution). Subsequent optimization with evolutionary algorithms identified operating conditions that reduce specific energy ...
Anke Bardehle, Andreas Limper, Ulrich Giese, Carlos Lucke, Mario Beiner, Christoph Gögelein, Lisa Leuchtenberger‐Engel, Christian Hopmann   +7 more
wiley   +1 more source

The reciprocal elastic net

Communications in Statistics: Case Studies, Data Analysis and Applications, 2023
Rahim Alhamzawi, Ahmed Alhamzawi, Himel Mallick   +2 more
openaire   +1 more source

Heteroscedastic Double Bayesian Elastic Net

CoRR
In many practical applications, regression models are employed to uncover relationships between predictors and a response variable, yet the common assumption of constant error variance is frequently violated. This issue is further compounded in high-dimensional settings where the number of predictors exceeds the sample size, necessitating ...
openaire   +2 more sources

Lasso and elastic nets by orthants

, 2023
44 pages, 10 figures, 3 ...
openaire   +2 more sources

Copper Nanocrystallization in Anodic Oxide Films of Ti–Cu‐Based Bulk Metallic Glass and Its Effect on the Corrosion Resistance and Cytocompatibility

Advanced Engineering Materials, EarlyView.
Viktoriia Shtefan, Thorgund Nemec, Ute Hempel, Annett Gebert and coworkers demonstrate that anodic treatment of Ti–Cu‐based metallic glass in a nontoxic pyrophosphate electrolyte forms a protective bilayered Ti/Zr‐oxide film enriched with Cu nanocrystals.
Viktoriia Shtefan, Nora Fernández Navas, Thorgund Nemec, Ivan Kaban, Ute Hempel, Andrea Voss, Volker Hoffmann, Darius Pohl, Annett Gebert   +8 more
wiley   +1 more source

Toward Knowledge‐Based Workflows: A Semantic Approach to Atomistic Simulations for Mechanical and Thermodynamic Properties

Advanced Engineering Materials, EarlyView.
Knowledge‐based atomistic workflows are presented for mechanical and thermodynamic properties. By coupling modular simulations with ontology‐aligned metadata and provenance, Fe case studies on elastic behavior, defects, thermal properties, and Hall–Petch strengthening reveal how FAIR, queryable, and reusable simulation data can be generated. Mechanical
Abril Azócar Guzmán, Hoang‐Thien Luu, Sarath Menon, Tilmann Hickel, Nina Merkert, Stefan Sandfeld   +5 more
wiley   +1 more source

Combinations of multimodal neuroimaging biomarkers and cognitive test scores to identify patients with cognitive impairment

Frontiers in Aging Neuroscience
BackgroundEarly detection of mild cognitive impairment (MCI), defined as the prodromal stage of dementia, is key to delaying the progression to dementia through lifestyle interventions and/or pharmacological treatments.
Yuriko Nakaoku, Soshiro Ogata, Kiyotaka Nemoto, Chikage Kakuta, Eri Kiyoshige, Kanako Teramoto, Kiyomasa Nakatsuka, Gantsetseg Ganbaatar, Masafumi Ihara, Kunihiro Nishimura   +9 more
doaj   +1 more source

Molecular Dynamics Studies of Shape Memory Polymers: From Bead–Spring Models to Atomistic Simulations

Advanced Engineering Materials, EarlyView.
Coarse‐grained (left) and atomistic (right) models of the shape memory polymer ESTANE ETE 75DT3 are shown schematically. The two representations bridge molecular detail and mesoscopic description. Both models capture shape memory behavior, linking segmental mobility and conformational relaxation of anisotropic chains to macroscopic recovery, and ...
Fathollah Varnik
wiley   +1 more source

Variable Selection for Survival Data with A Class of Adaptive Elastic\n Net Techniques [PDF]

, 2013
Md Hasinur Rahaman Khan, J.E. Shaw
openalex   +1 more source

Wilcoxon-type multivariate cluster elastic net

Neurocomputing
We propose a method for high dimensional multivariate regression that is robust to random error distributions that are heavy-tailed or contain outliers, while preserving estimation accuracy in normal random error distributions. We extend the Wilcoxon-type regression to a multivariate regression model as a tuning-free approach to robustness. Furthermore,
Mayu Hiraishi, Kensuke Tanioka, Hiroshi Yadohisa   +2 more
openaire   +2 more sources