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• W1993401069 abstract "With the increasing size and complexity of machines and vessels, the inverse problems of continuous bodies are becoming important. In this paper, the possibility of using a Multilayer Perceptron network trained with the Backpropagation Algorithm for detecting the critical flutter load and boundary conditions of tapered beams is studied. The beam model considered is a Timoshenko beam, which, with the use of the transfer matrix method, estimates the changes in various modal parameters caused by the shape parameters and boundary conditions of beams." @default.
• W1993401069 created "2016-06-24" @default.
• W1993401069 creator A5040763253 @default.
• W1993401069 date "1999-12-01" @default.
• W1993401069 modified "2023-09-27" @default.
• W1993401069 title "IDENTIFICATION FOR CRITICAL FLUTTER LOAD AND BOUNDARY CONDITIONS OF A BEAM USING NEURAL NETWORKS" @default.
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• W1993401069 doi "https://doi.org/10.1006/jsvi.1999.2451" @default.
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