Novos métodos determinísticos para gerar centros iniciais dos grupos no algoritmo fuzzy C-Means e variantes

Data clustering is applied to various fields such as data mining, image processing and pattern recognition technique. Clustering algorithms splits a data set into clusters such that elements within the same cluster have a high degree of similarity, while elements belonging to different clusters have a high degree of dissimilarity. The Fuzzy C-Means Algorithm (FCM) is a fuzzy clustering algorithm most used and discussed in the literature. The performance of the FCM is strongly affected by the selection of the initial centers of the clusters. Therefore, the choice of a good set of initial cluster centers is very important for the performance of the algorithm. However, in FCM, the choice of initial centers is made randomly, making it difficult to find a good set. This paper proposes three new methods to obtain initial cluster centers, deterministically, the FCM algorithm, and can also be used in variants of the FCM. In this work these initialization methods were applied in variant ckMeans.With the proposed methods, we intend to obtain a set of initial centers which are close to the real cluster centers. With these new approaches startup if you want to reduce the number of iterations to converge these algorithms and processing time without affecting the quality of the cluster or even improve the quality in some cases. Accordingly, cluster validation indices were used to measure the quality of the clusters obtained by the modified FCM and ckMeans algorithms with the proposed initialization methods when applied to various data sets

A biotecnologia na propagação e conservação do umbuzeiro (Spondias tuberosa Arr. Cam.) e percepção sobre sua importância por agricultores da comunidade Malhada Vermelha, Campo Redondo (RN-Brasil)

The umbu tree (Spondias tuberosa Arruda) is a fruit native to the northeast of Brazil with great economic, social and ecological importance for the northeastern semi-arid region. Despite its role, the umbu tree has suffered negative pressure thanks to cluttered extractivism and to negative selection of its fruits, which as the deforestation and the dormancy of seeds contribute to the decrease of its production year after year, making necessary studies that contribute to the improvement of this specie and its conservation. Given the risks to the conservation of the specie and its usefulness to the population, the association between plant biotechnology, for being a tool that can be used to increase its production. and the perception of gathering communities, by valuing the point of view and the knowledge of the population, can facilitate its conservation. This work aimed to develop methods of propagation for umbu tree as well as contribute to its conservation by using biotechnology, with specific objectives to contribute to the conservation of this species; determine concentrations of BAP and ANA in the formation of buds; testing the efficiency of different substrates and concentrations of gibberellic acid on germination in vitro and ex vitro, as well as capture the perception of families in communities that engage in the gathering of umbu. To study the germination, the seeds were inoculated in different substrates (vermiculite, vermiculite + clay, clay, clay + manure and manure + vermiculite) and in different concentrations of gibberellic acid (0 mg, 250 g and 500 mg). For the formation of buds BAP to 0.1 mg-1 was associated with different concentrations of ANA (0.2; 0.4; 0.8mg.L-1). The study of perception was conducted by applying semi-structured questionnaire with Malhada Vermelha community. The experiments resulted in vermiculite and concentration of 500 mg gibberellic acid as the best for germination. The association of 0.1 mg.L-1 of BAP to 0.2 mg.L-1 of ANA provided better formation of buds. As to the application of questionnaires, they revealed that the population understands the decreased amount of umbu plants and umbu fruit in the region, as well as shows concern for its conservation.

Uma aplicação do método fuzzy-electre-topsis para seleção de serviços de computação em nuvem

This work presents an application of a hybrid Fuzzy-ELECTRE-TOPSIS multicriteria approach for a Cloud Computing Service selection problem. The research was exploratory, using a case of study based on the actual requirements of professionals in the field of Cloud Computing. The results were obtained by conducting an experiment aligned with a Case of Study using the distinct profile of three decision makers, for that, we used the Fuzzy-TOPSIS and Fuzzy-ELECTRE-TOPSIS methods to obtain the results and compare them. The solution includes the Fuzzy sets theory, in a way it could support inaccurate or subjective information, thus facilitating the interpretation of the decision maker judgment in the decision-making process. The results show that both methods were able to rank the alternatives from the problem as expected, but the Fuzzy-ELECTRE-TOPSIS method was able to attenuate the compensatory character existing in the Fuzzy-TOPSIS method, resulting in a different alternative ranking. The attenuation of the compensatory character stood out in a positive way at ranking the alternatives, because it prioritized more balanced alternatives than the Fuzzy-TOPSIS method, a factor that has been proven as important at the validation of the Case of Study, since for the composition of a mix of services, balanced alternatives form a more consistent mix when working with restrictions.