Uma nova forma de calcular os centros dos Clusters em algoritmos de agrupamento tipo fuzzy c-means

Clustering data is a very important task in data mining, image processing and pattern recognition problems. One of the most popular clustering algorithms is the Fuzzy C-Means (FCM). This thesis proposes to implement a new way of calculating the cluster centers in the procedure of FCM algorithm which are called ckMeans, and in some variants of FCM, in particular, here we apply it for those variants that use other distances. The goal of this change is to reduce the number of iterations and processing time of these algorithms without affecting the quality of the partition, or even to improve the number of correct classifications in some cases. Also, we developed an algorithm based on ckMeans to manipulate interval data considering interval membership degrees. This algorithm allows the representation of data without converting interval data into punctual ones, as it happens to other extensions of FCM that deal with interval data. In order to validate the proposed methodologies it was made a comparison between a clustering for ckMeans, K-Means and FCM algorithms (since the algorithm proposed in this paper to calculate the centers is similar to the K-Means) considering three different distances. We used several known databases. In this case, the results of Interval ckMeans were compared with the results of other clustering algorithms when applied to an interval database with minimum and maximum temperature of the month for a given year, referring to 37 cities distributed across continents

Clusters locais de responsabilidade social das organizações: possibilidades e limites em debate

O presente artigo trata do papel das empresas no desenvolvimento social e econômico, considerando para tal as análises que envolvem a temática da Responsabilidade Social Empresarial numa perspectiva integrada a ações sociais de entidades governamentais e ONGs. Nesse sentido, o conceito de clusters de RS pressupõe que aglomerações de empresas, localizadas num mesmo território, estabeleçam interações entre si e com outros atores locais para otimizar práticas conjuntas de RS voltadas para o desenvolvimento sustentado da região, numa perspectiva integrada e global. As possibilidades interventivas dos clusters de RS podem expressar um avanço nos resultados das ações sociais e/ou ambientais empreendidas através de redes integradas

Desenvolvimento territorial no Rio Grande do Norte: uma identificação de clusters rurais

The general objective of this study is the identification of rural spaces in Rio Grande do Norte through a territorial approach. It looks if there is spatial correlations between municipalities that influence and are influenced by the rural environment, allowing the identification of clusters. To accomplish this objective it`s used, in the methodology, the factor analysis of principal components to achieve the indicators of rurality and territorial development, that deal with four dimensions of analysis: environmental, political-institutional, economical and spatial. Moreover, to identify the spatial correlations structure between municipalities it used the Moran index to both rurality and territorial development, leading to clustering identification. The results show that the rurality is present in most of Rio Grande do Norte municipalities, except in cases like Mossoró, Pau dos Ferros, Caicó and Natal, where can be regional dynamic poles. It is also verified that the more rural municipalities tend to be less developed, according to the territorial development index, and have less correlations with neighboring municipalities