Descriptive Profiles for Sets of Alternatives in Multiple Criteria Decision Aid

International audienceIn the context of Multiple Criteria Decision Aid, a decision-maker may be faced at any time with the task of analyzing one or several sets of alternatives, irrespective of the decision he is about to make. As in this case the alternatives may express contrasting gains and losses on the criteria on which they are evaluated, and while the sets that are presented to the decision-maker may potentially be large, the task of analysing them becomes a difficult one. Therefore the need to reduce these sets to a more concise representation is very important. Classically, profiles that describe sets of alternatives may be found in the context of the sorting problem, however they are either given beforehand by the decision-maker or determined from a set of assignment examples. We would therefore like to extend such profiles, as well as propose new ones, in order to characterize any set of alternatives. For each of them, we present several approaches for extracting them, which we then compare with respect to their performance

Combining machine learning and metaheuristics algorithms for classification method PROAFTN

© Crown 2019. The supervised learning classification algorithms are one of the most well known successful techniques for ambient assisted living environments. However the usual supervised learning classification approaches face issues that limit their application especially in dealing with the knowledge interpretation and with very large unbalanced labeled data set. To address these issues fuzzy classification method PROAFTN was proposed. PROAFTN is part of learning algorithms and enables to determine the fuzzy resemblance measures by generalizing the concordance and discordance indexes used in outranking methods. The main goal of this chapter is to show how the combined meta-heuristics with inductive learning techniques can improve performances of the PROAFTN classifier. The improved PROAFTN classifier is described and compared to well known classifiers, in terms of their learning methodology and classification accuracy. Through this chapter we have shown the ability of the metaheuristics when embedded to PROAFTN method to solve efficiency the classification problems

Electre Methods: Main Features and Recent Developments

We present main characteristics of Electre family methods, designed for multiple criteria decision aiding. These methods use as a preference model an outranking relation in the set of actions - it is constructed in result of concordance and non-discordance tests involving a specific input preference information. After a brief description of the constructivist conception in which the Electre methods are inserted, we present the main features of these methods. We discuss such characteristic features as: the possibility of taking into account positive and negative reasons in the modeling of preferences, without any need for recoding the data; using of thresholds for taking into account the imperfect knowledge of data; the absence of systematic compensation between "gains" and "losses". The main weaknesses are also presented. Then, some aspects related to new developments are outlined. These are related to some new methodological developments, new procedures, axiomatic analysis, software tools, and several other aspects. The paper ends with conclusions

Optical fiber characterization by simultaneous measurement of the transmitted and refracted near field

An experimental setup is presented which permits, in a routine way for R&D purposes, simultaneous measurement of the transmitted near field at 1300 nm and 1550 nm, and the refracted near field at 820 nm. A new method for the calibration of the refractive index is proposed. The obtained accuracy for the refractive index is dn+or-0.0002. The reproducibility of measurements of geometrical parameters like the mode field diameter, the core and cladding diameters, and concentricity error, is +or-0.1 mu m. Measurements of the mode field as a function of polarization state for four different hi-bi fiber are presented

Influence des caractéristiques du plasma initiateur sur la formation des couches minces d'oxydes de cuivre dans la pulvérisation cathodique réactive

Thin layers of copper oxides are prepared by condensation on fused quartz in a weakly ionized argon-oxygen plasma, of products initiated by cathode sputtering. The influence of discharge potential, and characteristics of the plasma, upon the nature of the layers are studied.Des couches minces d'oxydes de cuivre sont obtenues par condensation sur des supports en quartz des produits de réaction initiés dans des plasmas faiblement ionisés composés d'oxygène et d'argon, par pulvérisation cathodique de cuivre. On montre l'influence du plasma initiateur sur la nature des couches obtenues ainsi que le rôle du potentiel de décharge de la cathode

Experimental investigations of the statistical properties of polarization mode dispersion in single mode fibers

Polarization mode dispersion of installed optical cables and of short concatenations of hi-bi fibers have been measured with polarimetric and interferometric instruments. The results confirm the theoretical models, in particular the predicted relations between the two measurement methods. The importance of a statistical treatment of polarization mode dispersion is underscored by the observed instability of the principal states and the remarkable long-term stability of their statistics