Titlebook: Information Technology, Systems Research, and Computational Physics; Piotr Kulczycki,Janusz Kacprzyk,Rafal Wisniewski Conference proceedin

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Recurrent Neural Networks with Grid Data Quantization for Modeling LHC Superconducting Magnets Behaverconducting magnets. High resolution data available in Post Mortem database was used to train a set of models and compare their performance with respect to various hyper-parameters such as input data quantization and number of cells. A novel approach to signal level quantization allowed to reduce a

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Advances in Intelligent Systems and Computinghttp://image.papertrans.cn/i/image/465733.jpg

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Metaheuristics in Physical Processes Optimizationpared evolutionary algorithm (EA) - to find the approximate solution of the Wessinger’s equation, which is a nonlinear, first order, ordinary differential equation. Both methods were compared as an ANN training tool. Then, application of this method in selected physical processes is discussed.