In this paper, clustering-based rule generation methods for fuzzy classifier using non-parametric Autonomous Data Partitioning algorithm have been proposed. ADP-algorithm is used to determine the number of clusters fo...
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In this paper, clustering-based rule generation methods for fuzzy classifier using non-parametric Autonomous Data Partitioning algorithm have been proposed. ADP-algorithm is used to determine the number of clusters fo...
In this paper, clustering-based rule generation methods for fuzzy classifier using non-parametric Autonomous Data Partitioning algorithm have been proposed. ADP-algorithm is used to determine the number of clusters for use in various k-means-like clustering algorithms. Proposed method contributes to solving the problem of determining optimal number of clusters/rules. The efficiency of fuzzy classifiers with rules constructed by the specified algorithms has been tested on data sets from the KEEL repository. Experimental results show that proposed method outperforms baseline algorithm (the extremums rulebase generation algorithm) both in terms of classification accuracy and geometric mean metrics.
Context. Microlensing events provide a unique way to detect and measure the masses of isolated, non-luminous objects, particularly dark stellar remnants. Under certain conditions, it is possible to measure the mass of...
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This paper presents two Fault Detection and Isolation (FDI) methods for a brushless DC motor (BLDC) nanosatellite actuator. The main objective is to compare a classical multi-model FDI strategy with a method based on ...
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This paper presents two Fault Detection and Isolation (FDI) methods for a brushless DC motor (BLDC) nanosatellite actuator. The main objective is to compare a classical multi-model FDI strategy with a method based on Neural Network approach. The FDI algorithms must detect any error occurring in the Attitude Determination and control System (ADCS) of the satellite and then to assign it to a possible fault scenario. The performances of the two fault detection algorithms are analysed and compared considering external disturbances acting on the satellite motion. Moreover, this paper highlights the fact that a FDI based on neural networks can be successfully used as a redundant method for the satellite FDI subsystem.
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