Zsolt Alfréd Polgár, Andrei Ciprian Hosu, Zsuzsanna Ilona Kiss and Mihály Varga
Multi-access and heterogeneous wireless communications are considered to be one of the solutions for providing generalized mobility, high system efficiency and improved user experience, which are important characteristics of the Next Generation Networks. This paper proposes a Vertical Handover (VHO) decision algorithm for heterogeneous network architectures which integrate both cellular networks and Wireless Local Area Networks (WLANs). The cellular-WLAN and WLAN-WLAN VHO decisions are taken based on parameters which characterize both the coverage and the traffic load of the WLANs. Computer simulations performed in complex scenarios show that the proposed algorithm ensures better performance compared to “classical” VHO decision algorithms.
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The aim of the study was to test the ability to model soil capability units diversity of on the basis of limited information about particle size and morphology of the terrain data. The data obtained from digitization of maps of agricultural soil and topography of the region of the Upper Silesian Industrial District. Rule extraction tools and build models were algorithms in the field of computational intelligence: different versions of decision trees, neural networks and deep learning algorithms. The best algorithms allow for correct classification to 90% of the elements of the validation set. The design ensemble of specialized classifier algorithm increased the efficiency of decision-making algorithm to identify a set of validation to about 94%. Proper selection decision algorithm allows the estimation of the likelihood vector belonging to a complex object. Computational intelligence algorithms can be considered as a tool for extracting classification rules from the collection of data on soils on the local or regional level.
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decision making for the initiation of renal replacement therapy (RRT) in patients with AKI. Selected studies demonstrated that NGAL, cystatin-C, NAG, KIM-1, and a1-microglobulin had the potential to distinguish patients in whom RRT will be needed. This would imply that these biomarkers may be integrated into clinical decisionalgorithms, and could synergistically improve current ability to initiate RRT early.[ 16 , 17 ] However, published studies have many recognized limitations, which preclude the ability to adapt their findings into clinical practice today. While the