Titlebook: Cybernetics Approaches in Intelligent Systems; Computational Method Radek Silhavy,Petr Silhavy,Zdenka Prokopova Conference proceedings 2018

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书目名称Cybernetics Approaches in Intelligent Systems影响因子(影响力)学科排名




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书目名称Cybernetics Approaches in Intelligent Systems网络公开度学科排名




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书目名称Cybernetics Approaches in Intelligent Systems被引频次学科排名




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书目名称Cybernetics Approaches in Intelligent Systems读者反馈学科排名

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Interactive Control Systems for Mobile Cranes,s comprised of modules, output signals from which are sequentially transformed into a commands sequence corresponding to the motion strategy, related to incremental changes of position or motions depending on the distance to the end position. In the system, the commands sequence related to the posit

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A Harmony Search Algorithm to Solve the Manufacturing Cell Design Problem,sts on grouping machines and parts that they process, into groups called cells. So, the idea is to identify an organization of cells such that the number of times that a piece is transported between these cells is minimized. To this end, we use the HS optimization algorithm, which is based on the pr

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Decomposition Algorithms for Mathematical Programming and Generalization of the Dantzig-Wolfe Methoe function and constraints. Equivalent transformation of this problem is a task decomposition and coordination. This result allows to propose a new class of decomposition methods, which differ in approximating a feasible solution set of the coordination problem..The authors propose the modification

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Reliability Assessment of Safety Critical Intelligent Systems: Issues and Challenges,e-scale environmental damage, or considerable economic penalties. Some applications have strict time and cost constraints. Areas where these systems are used include military, weapon delivery systems, the space programs, manufacturing, control industry, robotics, transport, air traffic control, inte

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Multiple Feature Extraction and Multiple Classifier Systems in Face Recognition,le Classifier system (MFMC) has been presented for face recognition. At First, images are gathered from Cohn–Kanade database and segmented via masks. Then image features are extracted via Local Binary Pattern (LBP), gradient histogram and masks. For classifying extracted features, Naïve Bayes, K Nea