In supervised learning, the imbalanced number of instances among the classes in a dataset can make the algorithms to classify one instance from the minority class as one from the majority class. With the aim to solve ...In supervised learning, the imbalanced number of instances among the classes in a dataset can make the algorithms to classify one instance from the minority class as one from the majority class. With the aim to solve this problem, the KNN algorithm provides a basis to other balancing methods. These balancing methods are revisited in this work, and a new and simple approach of KNN undersampling is proposed. The experiments demonstrated that the KNN undersampling method outperformed other sampling methods. The proposed method also outperformed the results of other studies, and indicates that the simplicity of KNN can be used as a base for efficient algorithms in machine learning and knowledge discovery.展开更多
Santos Basin contains the major hub of oil and gas exploration in Brazil. Consequently, knowledge of ocean surface winds in this area is very important for operational and planning activities. In addition, the importa...Santos Basin contains the major hub of oil and gas exploration in Brazil. Consequently, knowledge of ocean surface winds in this area is very important for operational and planning activities. In addition, the importance of renewable energies is nowadays unquestionable, specifically in the case of the wind energy. In this paper, a data clustering technique is applied in order to obtain representative local wind patterns in Santos Basin. Reanalysis data from the National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR) have been used in this study.展开更多
The coastal marine habitats are often characterized by high biological activity. Therefore, monitoring programs and conservation plans of coastal environments are needed. So, in order to contribute to decision making ...The coastal marine habitats are often characterized by high biological activity. Therefore, monitoring programs and conservation plans of coastal environments are needed. So, in order to contribute to decision making process of the Brazilian Information System of Coastal Management, this paper presents a preliminary analysis of the effects of simulated deletions of individual organisms within a planktonic network as knowledge acquisition platform. An in situ scanning flow cytometer was used to data acquisition. A static and undirected food web is generated and represented by a fuzzy graph structure. Our results show through a series of indices the main changes of these networks. It was also verified similar traits and properties with other food webs found in the literature.展开更多
文摘In supervised learning, the imbalanced number of instances among the classes in a dataset can make the algorithms to classify one instance from the minority class as one from the majority class. With the aim to solve this problem, the KNN algorithm provides a basis to other balancing methods. These balancing methods are revisited in this work, and a new and simple approach of KNN undersampling is proposed. The experiments demonstrated that the KNN undersampling method outperformed other sampling methods. The proposed method also outperformed the results of other studies, and indicates that the simplicity of KNN can be used as a base for efficient algorithms in machine learning and knowledge discovery.
文摘Santos Basin contains the major hub of oil and gas exploration in Brazil. Consequently, knowledge of ocean surface winds in this area is very important for operational and planning activities. In addition, the importance of renewable energies is nowadays unquestionable, specifically in the case of the wind energy. In this paper, a data clustering technique is applied in order to obtain representative local wind patterns in Santos Basin. Reanalysis data from the National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR) have been used in this study.
文摘The coastal marine habitats are often characterized by high biological activity. Therefore, monitoring programs and conservation plans of coastal environments are needed. So, in order to contribute to decision making process of the Brazilian Information System of Coastal Management, this paper presents a preliminary analysis of the effects of simulated deletions of individual organisms within a planktonic network as knowledge acquisition platform. An in situ scanning flow cytometer was used to data acquisition. A static and undirected food web is generated and represented by a fuzzy graph structure. Our results show through a series of indices the main changes of these networks. It was also verified similar traits and properties with other food webs found in the literature.
