Abstract
The present work is inspired by laboratory experiments providing measurements in a few places of the hive for a long period of time. Based on Keller-Segel model in form of coupled nonlinear parabolic equations for the local temperature T and the bee density \(\rho \ge 0\), using the real data, we investigate numerically the thermoregulation in honey bee colonies in winter. We propose a numerical approach, based on conjugate gradient method into two stages: first, we solve a semilinear parabolic inverse problem to recover the density \(\rho \) and the temperature T. On the second stage we solve the strongly nonlinear convection-diffusion equation to recover again the density \(\rho \). The numerical tests show the efficiency of the method at the calibration of thermoregulation model.
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Acknowledgment
This work is supported by the Bulgarian National Science Fund under the Project KP-06-PN 46-7 “Design and research of fundamental technologies and methods for precision apiculture”.
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Atanasov, A.Z., Koleva, M.N., Vulkov, L. (2023). Numerical Optimization Identification of a Keller-Segel Model for Thermoregulation in Honey Bee Colonies in Winter. In: Simian, D., Stoica, L.F. (eds) Modelling and Development of Intelligent Systems. MDIS 2022. Communications in Computer and Information Science, vol 1761. Springer, Cham. https://doi.org/10.1007/978-3-031-27034-5_19
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