Results 121 to 130 of about 1,326,337 (292)

Testing for Bivariate Stochastic Dominance Using Inequality Restrictions [PDF]

In this paper, we propose of a test of bivariate stochastic dominance using a generalized framework for testing inequality constraints. Unlike existing tests, this test has the advantage of utilizing the covariance structure of the estimates of the joint
Thanasis Stengos, Brennan S. Thompson
core  

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

The Painted Wolf Decision Optimizer

Computers
This study introduces the Painted Wolf Decision Optimizer (PWO), the first deterministic, bio-inspired decision framework for discrete multi-criteria decision making (MCDM) derived from specific observed decision behaviors of African wild dogs, including
Shervin Zakeri, Dimitri Konstantas, Prasenjit Chatterjee   +2 more
doaj   +1 more source

SHADOW PRICE IMPLICATIONS OF SEVERAL STOCHASTIC DOMINANCE CRITERIA [PDF]

Stochastic dominance criteria can be, but seldom are explicitly, applied to problems having continuous variables. A previously developed model is modified to facilitate exploration of sets of shadow price vectors for decreasing (non-increasing) absolute ...
McCamley, Francis P., Rudel, Richard K.
core  

Ranking Alternatives on the Basis of a Dominance Intensity Measure [PDF]

, 2010
The additive multi-attribute utility model is widely used within MultiAttribute Utility Theory (MAUT), demanding all the information describing the decision-making situation. However, these information requirements can obviously be far too strict in many
Jiménez Martín, Antonio, Moreno Díaz, Arminda, Aguayo Garcia, Ernesto Aaron, Mateos Caballero, Alfonso   +3 more
core  

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

Improved Portfolio Choice using Second-Order Stochastic Dominance [PDF]

We examine the use of second-order stochastic dominance as both a way to measure performance and also as a technique for constructing portfolios. Using in-sample data, we construct portfolios such that their second-order stochastic dominance over a ...
James E. Hodder, Jens Carsten Jackwerth, Olga Kolokolova   +2 more
core  

Dominance solvable games with multiple payoff criteria [PDF]

, 2014
Two logically distinct and permissive extensions of iterative weak dominance are introduced for games with possibly vector-valued payoffs. The first, iterative partial dominance, builds on an easy-to-check condition but may lead to solutions that do not ...
Gerasimou, Georgios
core  

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

Advanced Engineering Materials, EarlyView.
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle, Cesar Alvarez‐Llamas, Vincent Motto‐Ros, Christophe Dujardin, Jérémie Margueritat, David Rodney   +5 more
wiley   +1 more source