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Titlebook: Advances in Computer Communication and Computational Sciences; Proceedings of IC4S Sanjiv K. Bhatia,Shailesh Tiwari,Munesh C. Trivedi Conf

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楼主: indulge
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Lecture Notes in Computer Scienceication problem. It is used in critical applications like cancer treatment for diagnosis and prognosis, analysis of gene expression and related areas. In earlier research works, various tumor clustering schemes were presented based on the single clustering systems and implemented successfully to a v
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Business Process Management Forumtional processes. For a viably and sorted out approach to drive the development in the realm of digitization is utilized by the approach of work process extraction. The work process extraction/mining is otherwise called process mining. The goal of workflow mining is to get the extraction of data of
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Carl Corea,Timotheus Kampik,Marco Montali analysis network is used to study the sea surface vessel detection algorithm. The visible image of the sea surface vessel is the input, the suspected target area is determined by the significance test, the PVANet model is extracted from the suspected target area, and the result is input into the su
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Simon James Jensen,Hugo A. López of a contaminated aquifer needs precise information of contaminant sources, usually only sparse and limited data are available. Therefore, often the process of remediation of contaminated groundwater is difficult and inefficient. This study utilizes Multivariate Adaptive Regression Splines (MARS) a
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Oskar Petto,Thomas Preindl,Martin Kjäerzation problems. Physical, chemical, or biological laws and rules have been utilized as source of inspiration for these algorithms. Studies on social behaviors of humans in recent years have shown that social processes, concepts, rules, and events can be considered and modeled as novel efficient met
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https://doi.org/10.1007/978-3-031-70445-1arly used in the field of healthcare for analyzing and detecting serious and complex conditions. Diabetes is one such condition that heavily affects the entire system. In this paper, application of intelligent machine learning algorithms like logistic regression, naïve Bayes, support vector machine,
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Peter A. François,Ralf Plattfautientific support for urban traffic guidance and control. As there is big forecast error when modeling toward traffic flow data with discrete grey model DGM (1, 1), this paper amends the equal interval time sequence. According to the characteristic of time coefficient and backpropagation (BP) neural
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https://doi.org/10.1007/978-3-031-70445-1 used for identification. The dependence of the identification accuracy on the number of intervals of the classifier splitting is investigated. The effect of the size of the training set from each user on the accuracy of identification is considered. Graphic dependencies of the identification error
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