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Titlebook: Artificial Intelligence and Soft Computing; 14th International C Leszek Rutkowski,Marcin Korytkowski,Jacek M. Zurad Conference proceedings

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Perioperative Antibiotikaprophylaxer generalizations, building on top of the existing knowledge, and even merging of these approaches. The paper is illustrated with selected examples of definitions, theorems, and proofs taken from rough and fuzzy set theory formulated in the Mizar language.
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Microarray , Gene Data Clustering by Means of Generalized Self-organizing Neural Networks with Evolvo be defined in advance. In the gene-based clustering of the considered data, our approach generates clusters that are easily divisible into subclusters related to particular sample classes. It corresponds, in a way, to subspace clustering that is highly desirable in microarray data analysis.
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Innovative Types and Abilities of Neural Networks Based on Associative Mechanisms and a New Associatto automatically interconnect representing similar or sequential data. This contribution describes generalized formulas for quick analytical computation of the structure and parameters of ANAKG neural graphs for representing and recalling of training sequences of objects.
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Initial Comparison of Formal Approaches to Fuzzy and Rough Setsr generalizations, building on top of the existing knowledge, and even merging of these approaches. The paper is illustrated with selected examples of definitions, theorems, and proofs taken from rough and fuzzy set theory formulated in the Mizar language.
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Conference proceedings 2015ft Computing, ICAISC 2015, held in Zakopane, Poland in June 2015. The 142 revised full papers presented in the volumes, were carefully reviewed and selected from 322 submissions. These proceedings present both traditional artificial intelligence methods and soft computing techniques. The goal is to
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Complexity of Shallow Networks Representing Finite Mappingsation of almost any randomly chosen function on a sufficiently large domain by a shallow network with perceptrons requires untractably large network. Concrete examples of such functions are constructed using Hadamard matrices.
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Extensions of Hopfield Neural Networks for Solving of Stereo-Matching Problemrly important: accuracy and computational time. For the experiment real and simulated stereo images are used. Obtained results lead to the conclusion about feasibility of considered architectures in the stereo matching problem solving for real time applications.
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Toward Work Groups Classification Based on Probabilistic Neural Network Approachemployee evaluation. In our approach, employee profiles are processed by a dedicated Radial Basis Probabilistic Neural Network based classifier, which finds non-explicit custom-created groups. The accuracy of the classifier is very high, revealing the potential efficacy of the proposed bio-inspired classification system.
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