Hyperspectral full‐field quick‐EXAFS imaging at the ROCK beamline for monitoring micrometre‐sized heterogeneity of functional materials under process conditions.

Autor: Briois, Valérie, Itié, Jean Paul, Polian, Alain, King, Andrew, Traore, Aliou Sadia, Marceau, Eric, Ersen, Ovidiu, La Fontaine, Camille, Barthe, Laurent, Beauvois, Anthony, Roudenko, Olga, Belin, Stéphanie

Publikováno v: Journal of Synchrotron Radiation; Sep2024, Vol. 31 Issue 5, p1084-1104, 21p

Dominance Based Crossover Operator for Evolutionary Multi-objective Algorithms

Autor: Roudenko, Olga, Schoenauer, Marc

Publikováno v: Dans Parallel Problem Solving from Nature 2004 [OAI oai:hal.inria.fr:inria-00000095_v1] - http://inria.ccsd.cnrs.fr/inria-00000095

In spite of the recent quick growth of the Evolutionary Multi-objective Optimization (EMO) research field, there has been few trials to adapt the general variation operators to the particular context of the quest for the Pareto-optimal set. The only

Externí odkaz: http://arxiv.org/abs/cs/0505080

Chemical Speciation by Quick‐XAS and Raman Spectroscopy: Validation of Two Cells for in situ Time‐Resolved Monitoring of the Impregnation and Drying of CoMoP/Al2O3 Catalysts.

Autor: Barata, Beatriz, Legens, Christèle, Devers, Elodie, Delpoux, Olivier, Barthe, Laurent, Roudenko, Olga, Briois, Valérie

Publikováno v: ChemCatChem; 4/6/2023, Vol. 15 Issue 7, p1-14, 14p

ROCK: A Beamline Tailored for Catalysis and Energy-Related Materials from ms Time Resolution to µm Spatial Resolution.

Autor: La Fontaine, Camille, Belin, Stephanie, Barthe, Laurent, Roudenko, Olga, Briois, Valerie

Publikováno v: Synchrotron Radiation News; Jan/Feb2020, Vol. 33 Issue 1, p20-25, 6p

A Steady Performance Stopping Criterion for Pareto-based Evolutionary Algorithms

Autor: Roudenko, Olga, Schoenauer, Marc

Publikováno v: 6th International Multi-Objective Programming and Goal Programming Conference
6th International Multi-Objective Programming and Goal Programming Conference, Apr 2004, Hammamet, Tunisia

International audience; The most commonly used stopping criterion in Evolutionary Multi-objective Algorithms is an a priori fixed number of generations (or evaluations). But it is rather difficult to speak about achieving a particular compromise betw

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::03303aa9adc362d2e27f3d69a47074d1
https://hal.inria.fr/hal-01909120