Research Outputs

Now showing 1 - 2 of 2
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    Publication
    Sustainable development goals analysis with ordered weighted average operators
    (MDPI, 2021) ;
    Ruiz-Morales, Betzabe
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    Espitia-Moreno, Irma
    ;
    Alfaro-Garcia, Victor
    The present research proposes a new method to analyze the sustainable development goals (SDGs) index using ordered weighted average (OWA) operators. To develop this method, five experts evaluated and designated the relative importance of each of the 17 SDGs defined by the United Nations (UN), and with the use of the OWA and prioritized OWA (POWA) operators, rankings were generated. With the results, it is possible to visualize that the ranking of countries can change depending on the weights related to each SDG because the OWA and POWA operator methods can capture the uncertainty of the phenomenon.
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    Publication
    Bonferroni probabilistic ordered weighted averaging operators applied to agricultural commodities’ price analysis
    (MDPI, 2020) ;
    Espinoza-Audelo, Luis
    ;
    Olazabal-Lugo, Maricruz
    ;
    Blanco-Mesa, Fabio
    ;
    Alfaro-Garcia, Victor
    Financial markets have been characterized in recent years by their uncertainty and volatility. The price of assets is always changing so that the decisions made by consumers, producers, and governments about different products is not still accurate. In this situation, it is necessary to generate models that allow the incorporation of the knowledge and expectations of the markets and thus include in the results obtained not only the historical information, but also the present and future information. The present article introduces a new extension of the ordered weighted averaging (OWA) operator called the Bonferroni probabilistic ordered weighted average (B-POWA) operator. This operator is designed to unify in a single formulation the interrelation of the values given in a data set by the Bonferroni means and a weighted and probabilistic vector that models the attitudinal character, expectations, and knowledge of the decision-maker of a problem. The paper also studies the main characteristics and some families of the B-POWA operator. An illustrative example is also proposed to analyze the mathematical process of the operator. Finally, an application to corn price estimation designed to calculate the error between the price of an agricultural commodity using the B-POWA operator and a leading global market company is presented. The results show that the proposed operator exhibits a better general performance than the traditional methods.