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Physical Sciences and Mathematics Commons™
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Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Inverse Problem For A Parabolic System, Reza Pourgholi, Amin Esfahani, Hassan D. Mazraeh
Inverse Problem For A Parabolic System, Reza Pourgholi, Amin Esfahani, Hassan D. Mazraeh
Applications and Applied Mathematics: An International Journal (AAM)
In this paper a numerical approach combining the least squares method and a genetic algorithm is proposed for the determination of the source term in an inverse parabolic system (IPS). A numerical experiment confirm the utility of this algorithm as the results are in good agreement with the exact data. Results show that a reasonable estimation can be obtained by the genetic algorithm within a CPU with clock speed 2.7 GHz.
Applying Gmdh-Type Neural Network And Genetic Algorithm For Stock Price Prediction Of Iranian Cement Sector, Saeed Fallahi, Meysam Shaverdi, Vahab Bashiri
Applying Gmdh-Type Neural Network And Genetic Algorithm For Stock Price Prediction Of Iranian Cement Sector, Saeed Fallahi, Meysam Shaverdi, Vahab Bashiri
Applications and Applied Mathematics: An International Journal (AAM)
The cement industry is one of the most important and profitable industries in Iran and great content of financial resources are investing in this sector yearly. In this paper a GMDH-type neural network and genetic algorithm is developed for stock price prediction of cement sector. For stocks price prediction by GMDH type-neural network, we are using earnings per share (EPS), Prediction Earnings Per Share (PEPS), Dividend per share (DPS), Price-earnings ratio (P/E), Earnings-price ratio (E/P) as input data and stock price as output data. For this work, data of ten cement companies is gathering from Tehran stock exchange (TSE) in …
Optimal Correction Of Infeasible System In Linear Equality Via Genetic Algorithm, S. Ketabchi, H. Moosaei, S. Fallahi
Optimal Correction Of Infeasible System In Linear Equality Via Genetic Algorithm, S. Ketabchi, H. Moosaei, S. Fallahi
Applications and Applied Mathematics: An International Journal (AAM)
This work is focused on the optimal correction of infeasible system of linear equality. In this paper, for correcting this system, we will make the changes just in the coefficient matrix by using l norm and show that solving this problem is equivalent to solving a fractional quadratic problem. To solve this problem, we use the genetic algorithm. Some examples are provided to illustrate the efficiency and validity of the proposed method.