Neural network approach to data-driven estimation of chemotactic sensitivity in the Keller-Segel model (Q2092227)
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scientific article; zbMATH DE number 7611040
| Language | Label | Description | Also known as |
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| English | Neural network approach to data-driven estimation of chemotactic sensitivity in the Keller-Segel model |
scientific article; zbMATH DE number 7611040 |
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Neural network approach to data-driven estimation of chemotactic sensitivity in the Keller-Segel model (English)
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2 November 2022
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The authors consider one-dimensional chemotaxis initial-boundary value problem and present a deep learning approach to approximate solutions of that problem. Error analysis and an inverse problem of prediction coefficients in the model are considered.
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one-dimensional chemotaxis
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approximate solution
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neural network
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