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Information Journal Paper

Title

Solving random inverse heat conduction problems using PSO and genetic algorithms

Pages

  49-70

Abstract

 The main purpose of this paper is to solve an inverse random differential equation problem using evolutionary algorithms. Particle Swarm Algorithm and Genetic Algorithm are two algorithms that are used in this paper. In this paper, we solve the inverse problem by solving the inverse random differential equation using Crank-Nicholson's method. Then, using the particle swarm optimization algorithm and the genetic algorithm, we solve them. The algorithms presented in this article have advantages over other old methods that have been presented so far. Implementing these algorithms is simpler, have less run time and produce better approximation. The numerical results obtained in this paper also show that the solutions obtained for the examples presented in the numerical results section are highly accurate and have less error. All of the algorithms in this paper to obtain the desired numeric results, have been implemented on the Pentium (R) Dual core E5700 processor at 3. 00 GHz.

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  • Cite

    APA: Copy

    Hossein Zade Shahbolaghi, I., POURGHOLI, R., Dana Mazraeh, h., & Tabasi, s.h.. (2019). Solving random inverse heat conduction problems using PSO and genetic algorithms. JOURNAL OF NEW RESEARCHES IN MATHEMATICS, 5(19 ), 49-70. SID. https://sid.ir/paper/257345/en

    Vancouver: Copy

    Hossein Zade Shahbolaghi I., POURGHOLI R., Dana Mazraeh h., Tabasi s.h.. Solving random inverse heat conduction problems using PSO and genetic algorithms. JOURNAL OF NEW RESEARCHES IN MATHEMATICS[Internet]. 2019;5(19 ):49-70. Available from: https://sid.ir/paper/257345/en

    IEEE: Copy

    I. Hossein Zade Shahbolaghi, R. POURGHOLI, h. Dana Mazraeh, and s.h. Tabasi, “Solving random inverse heat conduction problems using PSO and genetic algorithms,” JOURNAL OF NEW RESEARCHES IN MATHEMATICS, vol. 5, no. 19 , pp. 49–70, 2019, [Online]. Available: https://sid.ir/paper/257345/en

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