Jesús M. Doña

LAMA: A linguistic aggregation of majority additive operator

A problem that we had encountered in the aggregation process, is how to aggregate the elements that have cardinality >1. The purpose of this article is to present a new aggregation operator of linguistic labels that uses the cardinality of these elements, the linguistic aggregation of majority additive (LAMA) operator. We also present an extension of the LAMA operator under the two‐tuple fuzzy linguistic representation model.

Majority additive–ordered weighting averaging: A new neat ordered weighting averaging operator based on the majority process

A problem that we had encountered in the aggregation process is how to aggregate the elements that have cardinality greater than one. The most common operators used in the aggregation process produce reasonable results, but, at the same time, when the items to aggregate have cardinality greater than one, they may produce distributed problems. The purpose of this article is to present a new neat ordered weighting averaging (OWA) operator that uses the cardinality of these elements to calculate their weights.

Analysis of OWA operators in decision making for modelling the majority concept

The majority concept plays a main role in decision making processes where one of the main problems is to define a decision strategy which takes into account the individual opinions of the decision makers to produce an overall opinion which synthesizes the opinions of the majority of the decision makers. The reduction of the individual values into a representative value of majority is usually performed trough an aggregation process. The most common operator used in these processes is the OWA operator, in which the majority concept can be modelled using fuzzy logic and linguistic quantifiers. In this work the fusion processes and the semantic used for modelling the majority concept in the OWA operators are analyzed and compared in order to present different approach to obtain a feasible majority aggregation value for the decision making problem.

A Majority Model in Group Decision Making Using QMA-OWA Operators

Group decision‐making problems are situations where a number of experts work in a decision process to obtain a final value that is representative of the global opinion. One of the main problems in this context is to design aggregation operators that take into account the individual opinions of the decision makers. One of the most important operators used for synthesizing the individual opinions in a representative value of majority in the OWA operator, where the majority concept used aggregation processes, is modeled using fuzzy logic and linguistic quantifiers. In this work the semantic of majority used in OWA operators is analyzed, and it is shown how its application in group decision‐making problems does not produce representative results of the concept expressed by the quantifier. To solve this type of problem, two aggregation operators, QMA–OWA, are proposed that use two quantification strategies and a quantified normalization process to model the semantic of the linguistic quantifiers in the group decision‐making process.

Ischemia classification via ECG using MLP neural networks

AbstractThis paper proposes a two stage system based in neural network models to classify ischemia via ECG analysis. Two systems based on artificial neural network (ANN) models have been developed in order to discriminate inferolateral and anteroposterior ischemia from normal electrocardiogram (ECG) and other heart diseases. This method includes pre-processing and classification modules. ECG segmentation and wavelet transform were used as pre-processing stage to improve classical multilayer perceptron (MLP) network. A new set of about 800 ECG were collected from different clinics in order to create a new ECG Database to train ANN models. The best specificity of all models in the test phases was found as 88.49%, and the best sensitivity was obtained as 80.75%.

A genetic algorithm to design industrial materials

At present, the development of our society is still marked by the need for lighter and stronger structures with a minimum manufacturing cost. The materials that are responding best to these needs are composite materials and as a result, these are replacing many traditional materials such as steel, wood or aluminium. Designing composite materials is difficult because it involves designing the geometry of the element and composition. Traditionally, due to the limited knowledge of these materials, these design tasks have been based on approximate methods; the possibilities for creating composite materials is almost unlimited, characterization by testing is very expensive and it is difficult to apply the results to other contexts. Due to this fact, the whole design task relies on the ability of an expert to select the best combination based on their knowledge and experience. This paper presents and compares a genetic Algorithm to design industrial materials.

Strategic Assessment of Business

The stock market volatility and the actual stock exchange activity have increased the need of counting with effective methods on the part of financial analysts to achieve a division in relation to the investment actions, being also growing the demand of methodological instruments that reduce and minimize the risks and uncertainty when valuating financial actives and companies. These systems not only must use quantitative information but the inclusion of qualitative information must also bear heavily on them, as an improvement element in the adjustment of these valuating methods, with the aim of throwing a more well-conceived or less mistaken decision. In this work, we present an alternative strategic assessment of business based in quantitative information.

Analysis of the genetic algorithm Gamic for multicriteria classification of inventories

Gamic (Genetic Algorithm for Multi-criteria Inventory Classification) is analysed in this paper. It is shown how Gamic may produce rank reversal and how, because of this, it is not an appropriate classification method. Moreover, we propose a modification of this algorithm that does not generate rank reversal and does not need all the elements of the inventory in order to carry out the classification. The modification of Gamic that is proposed to solve the former problems consists of the change of the weighted product instead of the aggregation function of the weighted sum, in order to aggregate the priorities in the analytical hierarchy process (AHP), showing how the use of an aggregation function of weighted products in AHP produces both feasible solutions and known ones.