A study of changes in temperature profile of porous fin model using cuckoo search algorithm
Autor: | Muhammad Sulaiman, Waseem Waseem, Poom Kumam, Muhammad Asif Zahoor Raja, Saeed Islam, Rashid Nawaz, Muhammad Farooq, Muhammad Shoaib |
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Rok vydání: | 2020 |
Předmět: |
Partial differential equation
Mean squared error Artificial neural network Differential equation 020209 energy Computer Science::Neural and Evolutionary Computation General Engineering 02 engineering and technology Engineering (General). Civil engineering (General) 01 natural sciences 010305 fluids & plasmas Ordinary differential equation 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Boundary value problem TA1-2040 Cuckoo search Algorithm Metaheuristic Mathematics |
Zdroj: | Alexandria Engineering Journal, Vol 59, Iss 1, Pp 11-24 (2020) |
ISSN: | 1110-0168 |
DOI: | 10.1016/j.aej.2019.12.001 |
Popis: | For analysis of physical properties of different materials, rectangular porous fins are used to examine the heat transformation through a system. In this paper, a metaheuristic is combined with neural computing modelling to study the effects of temperature changes in a porous fin model. Cuckoo search algorithm is used as an efficient optimization technique to find the best weights to reduce the mean squared error in the required temperature profile. The governing partial differential equation is converted into a non-linear ordinary differential equation subject to certain boundary conditions. Two individual cases, of silicon nitride (Si3N4) and Aluminium (Al), are considered. In the proposed procedure, the Cuckoo Search(CS) algorithm is combined with the artificial neural network (ANN), namely CS-ANN, to solve the differential equations and obtain solutions with better accuracy. Keywords: Heat distribution, Porous fin, Artificial intelligence, Metaheuristics, Cuckoo search algorithm, Differential equations, Optimization problems |
Databáze: | OpenAIRE |
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