Selection of the Informative Input Parameters for the Inverse Neural-Network Models of Observed Systems
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Mathematical Sciences"
DOI: 10.1007/s10958-018-3844-7
Abstract: We consider the problem of determination of the parameters of a measurement grid, which guarantees the exactness and stability of the solution of the inverse problem. The choice of the points of measurements is performed… read more here.
Keywords: input parameters; parameters inverse; selection informative; inverse neural ... See more keywords
Determination of the input parameters for inelastic background analysis combined with HAXPES using a reference sample
Sign Up to like & getrecommendations! Published in 2018 at "Applied Surface Science"
DOI: 10.1016/j.apsusc.2017.06.081
Abstract: Abstract The recent progress in HAXPES combined with Inelastic Background Analysis makes this method a powerful, non-destructive solution to get quantitative information on deeply buried layers and interfaces at depths up to 70 nm. However, we… read more here.
Keywords: input parameters; parameters inelastic; analysis; reference ... See more keywords
Optimization of diesel engine performance and emission parameters of Karanja biodiesel-ethanol-diesel blends at optimized operating conditions
Sign Up to like & getrecommendations! Published in 2021 at "Fuel"
DOI: 10.1016/j.fuel.2021.120451
Abstract: Abstract This study reviews Karanja biodiesel, ethanol and diesel blending in context of Indian subcontinent and also focuses on its effects on engine’s performance, emission and combustion responses. Experimentations carried out on four stroke single… read more here.
Keywords: diesel; input parameters; engine; karanja biodiesel ... See more keywords
Inverse uncertainty quantification of reactor simulations under the Bayesian framework using surrogate models constructed by polynomial chaos expansion
Sign Up to like & getrecommendations! Published in 2017 at "Nuclear Engineering and Design"
DOI: 10.1016/j.nucengdes.2016.11.032
Abstract: Abstract Modeling and simulations are naturally augmented by extensive Uncertainty Quantification (UQ) and sensitivity analysis requirements in the nuclear reactor system design, in which uncertainties must be quantified in order to prove that the investigated… read more here.
Keywords: input parameters; expansion; uncertainty quantification; inverse ... See more keywords
Finite element analysis of the human mandible: a systematic review with meta-analysis of the essential input parameters
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-03959-9
Abstract: Human mandibular finite element analysis (FEA) requires essential parameters for proper simulation, namely: the forces, fixtures, material properties, and the boundary conditions. The purpose of this systematic review is to determine the evidence-based values of… read more here.
Keywords: systematic review; analysis; force; finite element ... See more keywords
Characterization of soybeans and calibration of their DEM input parameters
Sign Up to like & getrecommendations! Published in 2020 at "Particulate Science and Technology"
DOI: 10.1080/02726351.2020.1775739
Abstract: Abstract The main objective of this study is to calibrate Discrete Element Modeling (DEM) input parameters for Vietnamese DT84 variety soybeans. For this purpose, the shape of the soybeans was firstly analyzed through digital images… read more here.
Keywords: soybeans calibration; characterization soybeans; input parameters; dem input ... See more keywords
Performance analysis of unreliable manufacturing systems with uncertain reliability parameters estimated from production data
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Computer Integrated Manufacturing"
DOI: 10.1080/0951192x.2019.1644535
Abstract: ABSTRACT System engineering methods for the performance evaluation of manufacturing systems require the estimation of input parameters, which is either based on real data or experts’ knowledge. In both cases, the input parameters are subjected… read more here.
Keywords: input parameters; performance; unreliable manufacturing; manufacturing systems ... See more keywords
Influence of input parameters on the near-dry WEDM of Monel alloy
Sign Up to like & getrecommendations! Published in 2018 at "Materials and Manufacturing Processes"
DOI: 10.1080/10426914.2017.1279297
Abstract: ABSTRACT Near-dry wire electrical discharge machining (WEDM) is a modified WEDM process, which has no adverse effects on the environment, in which metal removals have been done with the dielectric medium being used in the… read more here.
Keywords: dry wedm; monel alloy; input parameters; near dry ... See more keywords
Inverse optimization of input parameters in sugar mill cogeneration using surrogates and metaheuristics
Sign Up to like & getrecommendations! Published in 2025 at "Journal of Modelling in Management"
DOI: 10.1108/jm2-05-2025-0240
Abstract: Cogeneration plants powered by bagasse offer an efficient way to meet the thermal and electrical demands of sugar mills. However, configuring input settings in real time to meet fluctuating power targets remains a complex operational… read more here.
Keywords: mill cogeneration; sugar mill; inverse optimization; input parameters ... See more keywords
Direct comparison of three residual risk models for hepatitis B virus window period infections using updated input parameters
Sign Up to like & getrecommendations! Published in 2020 at "Vox Sanguinis"
DOI: 10.1111/vox.12889
Abstract: Comparison of two models for estimating residual transfusion transmission risk by NAT screened window period (WP) donations in South African repeat donors gave identical results for HIV but not for HBV. In order to understand… read more here.
Keywords: window period; risk; input parameters; risk models ... See more keywords
Optimization of Inputs for the Application of ANN to Rail Track Granular Materials
Sign Up to like & getrecommendations! Published in 2024 at "Canadian Geotechnical Journal"
DOI: 10.1139/cgj-2024-0384
Abstract: Machine Learning (ML) models such as Artificial Neural Networks (ANN) have gained increasing popularity in geotechnical engineering applications as an alternative to conventional empirical and computational models. At present, very few ML models exist for… read more here.
Keywords: optimization inputs; application ann; granular materials; track granular ... See more keywords