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Titlebook: Hybrid Artificial Intelligent Systems; 13th International C Francisco Javier de Cos Juez,José Ramón Villar,Emi Conference proceedings 2018

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Improving Adaptive Optics Reconstructions with a Deep Learning Approachic turbulence effects. In the latest years, artificial intelligence methods were applied in this topic, with artificial neural networks becoming one of the reconstruction algorithms with better performance. These algorithms are developed to work with Shack-Hartmann wavefront sensors, which measures
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Complexity of Rule Sets in Mining Incomplete Data Using Characteristic Sets and Generalized Maximal induction we use characteristic sets and generalized maximal consistent blocks. Therefore we apply four different approaches for data mining. As follows from our previous experiments, where we used an error rate evaluated by ten-fold cross validation as the main criterion of quality, no approach is
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Optimization of the University Transportation by Contraction Hierarchies Method and Clustering Algorhicles by nodes and the optimal route for the university transport service. With the recent expansion of the facilities of a university institution, the allocation of the routes for the transport of its students, became more complex. As a result, geographic information systems (GIS) tools and operat
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Identification of Patterns in Blogosphere Considering Social Positions of Users and Reciprocity of Rtwork with already identified relationships between users which evolves in time. The social network is based on the Polish blog website pertaining on socio-political issues .. It consists of bloggers and links between them, which result from the intensity and characteristic features of posting comme
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Modelling and Forecasting of the , Radiation Level Time Series at the Canfranc Underground Laborator main distortion for obtaining high accuracy results. At Spain, the Canfranc Underground Laboratory hosts ground-breaking experiments, such as Argon Dark Matter-1t aimed at the dark matter direct searches. For the collaborations exploiting these experiments, the modelling and forecasting of the . le
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Distinctive Features of Asymmetric Neural Networks with Gabor Filterses are the nonlinear characteristics as the squaring and rectification functions, which are observed in the retinal and visual cortex networks. Conventional models for motion processing, are to use symmetric quadrature functions with Gabor filters. This paper proposes a new motion processing model o
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