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- An Algorithm to Discover the k-Clique Cover in Networks.Publication . Cavique, Luís; Mendes, Armando B.; Santos, Jorge M. A.In social network analysis, a k-clique is a relaxed clique, i.e., a kclique is a quasi-complete sub-graph. A k-clique in a graph is a sub-graph where the distance between any two vertices is no greater than k. The visualization of a small number of vertices can be easily performed in a graph. However, when the number of vertices and edges increases the visualization becomes incomprehensible. In this paper, we propose a new graph mining approach based on k-cliques. The concept of relaxed clique is extended to the whole graph, to achieve a general view, by covering the network with k-cliques. The sequence of k-clique covers is presented, combining small world concepts with community structure components. Computational results and examples are presented.
- Um algoritmo para encontrar a cobertura por k-cliques em redes sociaisPublication . Mendes, Armando B.; Cavique, Luís; Santos, Jorge M. A.Na análise de redes sociais, uma k-clique é a relaxação de uma clique, i.e., uma k-clique é um quase sub-grafo completo. Um k-clique num grafo é um sub-grafo onde a distancia entre quaisquer par de vértices não é maior que k. A visualização de um pequeno número de vértices é fácil de obter. Contudo, quando o número de vértices aumenta a visualização torna-se incompreensível. Nesta comunicação, propomos uma nova abordagem na extracção de conhecimento em grafos, utilizando k-cliques. O conceito que clique relaxado é estendido para todo o grafo, de forma a ter uma visão geral, ao cobrir a rede com k-cliques. Sequências de coberturas de k-cliques são apresentadas combinando o conceito dos "pequenos mundos" com estruturas com coesão. Resultados computacionais e exemplos são apresentados.
- Animal Grazing System EfficiencyPublication . Silva, Emiliana; Santos, Carlos; Mendes, Armando B.This chapter proposes to estimate the technical efficiency in agricultural grazing systemsgrazing systems (dairy, beef and mixed) in Azores, in the year 2002. This research used 184 agricultural farms of FADN – Farm Accountancy Data Network. DEA, a non-parametric methodology, was used to estimate efficiency by means of DEAP software. The results have shown that the average technical efficiency in the dairy grazing system was 63.2% (CRS) and was higher (71.4%) in VRS, and the scale efficiency was about 89.2%. In beef grazing system, the average technical efficiency (CRS) was 69.4%; VRS and the scale efficiency were 82.9 and 84.2%, espectively. In the mixed grazing system, the average technical efficiency (CRS) was 89%, the VRS was higher (99.24%) and the scale efficiency was 89.8%. The mixed system is the most efficient, and about half (46.7%) of the farms were efficient. In the dairy grazing system and in the beef systems, only 9.8 and 11.1% were efficient farms. The efficiency is generally higher in mixed systems than in dairy and beef systems.
- Apoiar decisões complexas.Publication . Mendes, Armando B."[…]. A discussão sobre a localização do novo aeroporto de Lisboa chama a atenção para uma área do apoio à decisão com distintos investigadores nacionais: a análise de decisão multicritério. Nesta metodologia, começa-se por definir um grupo de alternativas admissíveis (i.e., passíveis de serem colocadas em prática) e mutuamente exclusivas, de modo a apenas ser possível escolher uma e só uma delas, conhecidas por alternativas de decisão. Assim, decidir é escolher a melhor de entre o conjunto de alternativas de decisão pré-definido. A definição do conjunto de alternativas de decisão pode ser um processo complexo e demorado. […]".
- A aprendizagem de conceitos matemáticos fundamentados na sua etimologia e morfologiaPublication . Melo, Helena SousaMuitos conceitos matemáticos podem ser aprendidos e compreendidos utilizando a sua própria designação, ou seja, utilizando o conhecimento etimológico das palavras que o compõe. [...].
- Azorean Agriculture Efficiency by PARPublication . Mendes, Armando B.; Noncheva, Veska; Silva, EmilianaThe producers always aspire at increasing the efficiency of their production process. However, they do not always succeed in optimising their production. In the last years, the interest on Data Envelopment Analysis (DEA) as a powerful tool for measuring efficiency has increased. This is due to the large amount of data sets collected to better understand the phenomena under study and, at the same time, to the need of timely and inexpensive information. The "Productivity Analysis with R" (PAR) framework establishes a user-friendly data envelopment analysis environment with special emphasis on variable selection, aggregation, summarisation and interpretation of the results. The starting point is the following R packages: DEA (Diaz-Martinez and Fernandez-Menendez 2008) and FEAR (Wilson 2008). The DEA package performs some models of data envelopment analysis presented in Cooper et al. (2007). FEAR is a software package for computing nonparametric efficiency estimates and testing hypotheses in frontier models. FEAR implements the bootstrap methods described in Simar and Wilson (2000). PAR is a software framework using a portfolio of models for efficiency estimation and also providing results explanation functionality. PAR framework has been developed to distinguish between efficient and inefficient observations and to explicitly advise the producers about possibilities for production optimisation. PAR framework offers several R functions for a reasonable interpretation of the data analysis results and text presentation of the obtained information. The output of an efficiency study with PAR software is self-explanatory. We are applying PAR framework to estimate the efficiency of the agricultural system in Azores (Mendes et al. 2009). All Azorean farms will be clustered into homogeneous groups according to their efficiency measurements to define clusters of "good" practices and cluster of "less good" practices. This makes PAR appropriate to support public policies in agriculture sector in Azores.
- BI and data warehouse solutions for energy production industry: application of the CRISP-DM methodology.Publication . Mendes, Armando B.This paper reports two projects for supporting decisions of the Company of Electricity in Azores Islands, Electricidade dos Açores. There were several decisions to support, such as whether communications between islands should moved from the present telephone lines to VoIP, and if better models to support forecast power consumption should be adopted. The solution established integrates OLAP cubes in a data mining project, based on CRISP-DM process model. Both for strategic and more operational decisions the objective was always to get accurate data, build a data warehouse and to get tools to analyze it in order to properly inform the decision makers. These DSS's translates big CSV flat files or acquire data in real time from operational Data Bases to update a data warehouse, including importing, evaluating data quality and populating relational tables. Multidimensional data cubes with numerous dimensions and measures were used for operational decisions and as exploration tools in the strategic ones. Data mining models for forecasting, clustering, decision trees and association rules identified several inefficient procedures and even fraud situations. Not only was possible to support the necessary decisions, but several models were also displayed so that control decision makers and strategists could support new problems.
- Canonical Correlation Analysis in Variable Aggregation in DEA.Publication . Mendes, Armando B.; Noncheva, Veska; Silva, EmilianaNeste trabalho documenta-se a aplicação de análise de correlações canónicas à agregação de variáveis em DEA, usando as correlações entre as variáveis originais e os componentes canónicos extraídos. É apresentado um caso de estudo que utiliza um pequeno conjunto de dados sobre explorações agrícolas na ilha terceira. Neste conjunto de 30 explorações agrícolas pretende-se usar 17 variáveis de input e 2 de output para avaliar a eficiência usando DEA. Sem qualquer redução de dados, vários problemas conhecidos como "praga da dimensionalidade" seriam esperados. Com os procedimentos sugeridos foi possível obter resultados razoáveis e de acordo com o conhecimento de domínio actual.
- Classificação hierárquica de dados intervalares da indústria automóvel com o coeficiente de afinidadePublication . Sousa, Áurea; Bacelar-Nicolau, Helena; Silva, Osvaldo; Nicolau, Fernando C.São mostradas as estruturas classificatórias mais relevantes, obtidas com a Análise Classificatória Hierárquica de um conjunto de dados retirado da literatura da análise de dados complexos, referentes a modelos de carros (Car data set), com base no coeficiente de afinidade generalizado, ponderado, centrado e reduzido pelo método de Wald e Wolfowitz, e em critérios de agregação probabilísticos no âmbito da Metodologia VL. Comparam-se os resultados obtidos com os de outros autores e diferentes métodos, bem como com uma partição definida a priori. Os métodos utilizados foram capazes de detetar classes consistentes e consonantes de macro-dados, quer com a partição a priori quer com os resultados de outros autores, e enquadram-se nas metodologias de Análise de Dados Simbólicos (ADS), sendo de salientar que as agregações implícitas nessas abordagens permitem o tratamento de bases de micro-dados (dados não agregados) de grande dimensão.
- Clustering Validation in the Context of Hierarchical Cluster Analysis: an Empirical StudyPublication . Silva, Osvaldo Dias Lopes da; Sousa, Áurea; Bacelar-Nicolau, HelenaABSTRACT: The evaluation of clustering structures is a crucial step in cluster analysis. This study presents the main results of the hierarchical cluster analysis of variables concerning a real dataset in the context of Higher Education. The goal of this research is to find a typology of some relevant items taking into account both the homogeneity and the isolation of the clusters.Two similarity measures, namely the standard affinity coefficient and Spearman’s correlation coefficient, were used, and combined with three probabilistic (AVL, AVB and AV1) aggregation criteria, from a parametric family in the scope of the VL (Validity Link) methodology. The best partitions were selected based on some validation indices, namely the global STAT levels statistics and the measures P(I2, Σ) and , adapted to the case of similarity coefficients. In order to evaluate the clusters and identify their most representative elements, the Mann and Whitney U statistics and the silhouette plot were also used.