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Author: Amirgaliyev Y.N. × search.filters.applied.f.dc.language.iso: en ×

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Now showing 1 - 3 of 3
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    ItemOpen Access
    ENSEMBLE LEARNING ALGORITHMS IN PATTERN RECOGNITION TASKS
    (Suleyman Demirel University, 2016) Aitbayev Y.K.; Kabulov B.M.; Amirgaliyev Y.N.
    The article is devoted to the topic of using models of collective decision-making in automated intelligent systems. Under consideration application of these models to solve image recognition problems. Under collective recognition implies the task of using a set of classifiers , each of which decides on the class of one entity with subsequent coordination of solutions using some algorithm.
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    ItemOpen Access
    USING ANDROID TO IMPLEMENT INTELLIGENT TESTING SYSTEM
    (faculty of engineering and natural sciences, 2013) Amirgaliyev Y.N.; Kutlu A.; Bogdanchikov A.V.; Latuta K.N.; Suliyev R.N.
    The first part of the paper discusses the role of mobile applications in person’s life and proposes a method to apply testing system in Android device. The second part of the paper describes the algorithm used in the prototypes of the testing system. The third part explains details of each prototype and their key concepts. In conclusion the two prototypes are compared and advantages of each are highlighted
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    ItemOpen Access
    ENSEMBLE LEARNING ALGORITHMS IN PATTERN RECOGNITION TASKS
    (СДУ хабаршысы - 2017, 2017) Kabulov B.M.; Aitbayev Y.K. ; Amirgaliyev Y.N.
    Abstract. There has been growing interest in pattern recognition tasks in the last decade. This is determined by the prevalence of the problems that is being solved in recognizing images and characters, scene analysis, technical and medical diagnostics, signal identification, analysis of expert data, speech recognition, creation of expert and artificial intelligence systems. The article is devoted to the topic of collective decision-making models in automated intellectual systems. The application of such models for pattern recognition problems is being considered. What is meant by the term «collective recognition» is the task of using multiple classifiers, each of which will decide on the class of one entity with the subsequent coordination of their decisions with the help of a certain algorithm.