TY - GEN
T1 - A method for solving the time fractional heat conduction inverse problem based on ant colony optimization and artificial bee colony algorithms
AU - Brociek, Rafał
AU - Słota, Damian
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - The paper presents an application of ant colony optimization and artificial bee colony algorithms to solve the inverse heat conduction problem of fractional order. In a given fractional heat conduction model, one of the parameters – thermal conductivity coefficient is missing. With output of the model - temperature measurements, functional defining error of approximate solution is created. In order to reconstruct thermal conductivity coefficient we apply swarm intelligence algorithms to minimize created functional.
AB - The paper presents an application of ant colony optimization and artificial bee colony algorithms to solve the inverse heat conduction problem of fractional order. In a given fractional heat conduction model, one of the parameters – thermal conductivity coefficient is missing. With output of the model - temperature measurements, functional defining error of approximate solution is created. In order to reconstruct thermal conductivity coefficient we apply swarm intelligence algorithms to minimize created functional.
KW - Ant colony algorithm
KW - Artificial bee colony algorithm
KW - Fractional heat conduction equation
KW - Inverse problem
UR - https://www.scopus.com/pages/publications/85030854354
U2 - 10.1007/978-3-319-67642-5_29
DO - 10.1007/978-3-319-67642-5_29
M3 - Conference contribution
AN - SCOPUS:85030854354
SN - 9783319676418
T3 - Communications in Computer and Information Science
SP - 351
EP - 361
BT - Information and Software Technologies - 23rd International Conference, ICIST 2017, Proceedings
A2 - Damasevieius, Robertas
A2 - Mikasyte, Vilma
PB - Springer Verlag
T2 - 23rd International Conference on Information and Software Technologies, ICIST 2017
Y2 - 12 October 2017 through 14 October 2017
ER -