1000 resultados para Estadística e Investigación Operativa


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En MAUT uno de los modelos más usados para representar las preferencias de los decisores es el modelo de utilidad multiatributo aditivo. En muchos problemas reales la determinación de las funciones de utilidad y pesos de cada atributo no pueden ser obtenidos de una forma precisa. En este trabajo consideramos que la imprecisión en las funciones de utilidad queda representada al considerar clases de funciones de utilidad, y la de los pesos mediante una ordenación de los mismos, intervalos de pesos, distribuciones de probabilidad normales o números difusos. La metodología que proponemos para resolver los problemas multiatributo imprecisos está basada en la intensidad de dominancia entre pares de alternativas. Partiendo de la matriz de dominancia se calcula para cada alternativa el valor de dominancia total, en función de la intensidad con la que esta alternativa domina al resto y el resto la domina a ella, el cual nos permitirá obtener la ordenación de las alternativas.

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Tema 1. Variables aleatorias discretas. Binomial. Poisson.

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Contraste de Bondad de Ajuste de distribuciones discretas. Método de Chi-Cuadrado (para contrastar el ajuste a una Binomial).

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Este artículo pretende ofrecer una visión panorámica de la contribución original de los matemáticos nacidos en el actual territorio español durante el último milenio, analizando las causas de que dicha contribución haya sido inferior a la de países de tamaño, desarrollo económico y poder político semejantes.

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Cálculo estimadores CM y denominadores de la F en los análisis de ANOVA multifactorial.

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Citizens demand more and more data for making decisions in their daily life. Therefore, mechanisms that allow citizens to understand and analyze linked open data (LOD) in a user-friendly manner are highly required. To this aim, the concept of Open Business Intelligence (OpenBI) is introduced in this position paper. OpenBI facilitates non-expert users to (i) analyze and visualize LOD, thus generating actionable information by means of reporting, OLAP analysis, dashboards or data mining; and to (ii) share the new acquired information as LOD to be reused by anyone. One of the most challenging issues of OpenBI is related to data mining, since non-experts (as citizens) need guidance during preprocessing and application of mining algorithms due to the complexity of the mining process and the low quality of the data sources. This is even worst when dealing with LOD, not only because of the different kind of links among data, but also because of its high dimensionality. As a consequence, in this position paper we advocate that data mining for OpenBI requires data quality-aware mechanisms for guiding non-expert users in obtaining and sharing the most reliable knowledge from the available LOD.

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El éxito en la búsqueda de conocimiento a partir de grandes cantidades de datos radica en la calidad de los mismos. Hasta ahora los aspectos de calidad de los datos se han enfocado principalmente a la limpieza de los datos: detección de duplicados, valores atípicos, perdidos, incompletos o conflictos en instancias, entre otros. En este trabajo se presenta un caso de estudio que nos ha permitido determinar ciertos aspectos de calidad que pueden mejorar la expectativa de éxito en el análisis evitando resultados erróneos, incorrectos o poco fiables. Este es un primer paso hacia la consideración de manera sistemática y estructurada de criterios de calidad específicos para minería de datos que ayude al minero de datos en sus objetivos.

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Comunicación presentada en las XVI Jornadas de Ingeniería del Software y Bases de Datos, JISBD 2011, A Coruña, 5-7 septiembre 2011.

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In this paper we describe an hybrid algorithm for an even number of processors based on an algorithm for two processors and the Overlapping Partition Method for tridiagonal systems. Moreover, we compare this hybrid method with the Partition Wang’s method in a BSP computer. Finally, we compare the theoretical computation cost of both methods for a Cray T3D computer, using the cost model that BSP model provides.

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The so-called parallel multisplitting nonstationary iterative Model A was introduced by Bru, Elsner, and Neumann [Linear Algebra and its Applications 103:175-192 (1988)] for solving a nonsingular linear system Ax = b using a weak nonnegative multisplitting of the first type. In this paper new results are introduced when A is a monotone matrix using a weak nonnegative multisplitting of the second type and when A is a symmetric positive definite matrix using a P -regular multisplitting. Also, nonstationary alternating iterative methods are studied. Finally, combining Model A and alternating iterative methods, two new models of parallel multisplitting nonstationary iterations are introduced. When matrix A is monotone and the multisplittings are weak nonnegative of the first or of the second type, both models lead to convergent schemes. Also, when matrix A is symmetric positive definite and the multisplittings are P -regular, the schemes are also convergent.

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The objective of this paper is to develop a method to hide information inside a binary image. An algorithm to embed data in scanned text or figures is proposed, based on the detection of suitable pixels, which verify some conditions in order to be not detected. In broad terms, the algorithm locates those pixels placed at the contours of the figures or in those areas where some scattering of the two colors can be found. The hidden information is independent from the values of the pixels where this information is embedded. Notice that, depending on the sequence of bits to be hidden, around half of the used pixels to keep bits of data will not be modified. The other basic characteristic of the proposed scheme is that it is necessary to take into consideration the bits that are modified, in order to perform the recovering process of the information, which consists on recovering the sequence of bits placed in the proper positions. An application to banking sector is proposed for hidding some information in signatures.