Yıl 2021,
Cilt: 4 Sayı: 1, 11 - 18, 03.01.2022
Alla Saad
,
Hisham Mohammed
Kaynakça
- K. Abbo and M. S Jaborry, Learning rate for the back propagation algorithm based on modified scant equation, Iraqi J. Stat. Sci., 14(26) 2014, 1–11.
- Y. A. Laylani, K. K. Abbo, and H. M. Khudhur, Training feed forward neural network with modified Fletcher-Reeves method, Journal of Multidisciplinary Modeling and Optimization, 1(1) 2018, 14–22.
- A. Antoniou and W.-S. Lu, Practical Optimization: Algorithms and Engineering Applications. Springer Science & Business Media, 2007.
- J. Nocedal and S. Wright, Numerical Optimization. Springer Science & Business Media, 2006.
- E. Polak and G. Ribiere, “Note sur la convergence de méthodes de directions conjuguées,” ESAIM Math. Model. Numer. Anal. Mathématique Anal. Numérique, 3(R1) 1969, 35-43.
- M. R. Hestenes and E. Stiefel, Methods of conjugate gradients for solving linear systems, J. Res. Nat. Bur. Stand.,49 (1) 1952, 409-436.
- R. Fletcher and C. M. Reeves, Function minimization by conjugate gradients, Comput. J., 7(2) 1964, 149-154.
- Y. H. Dai and Y. Yuan, A nonlinear conjugate gradient method with a strong global convergence property, SIAM J. Optim., 10(1) 1999, 177-182.
- L. C. W. Dixon, Conjugate gradient algorithms: quadratic termination without linear searches, IMA J. Appl. Math., 15(1) 1975, 9-18.
- K. K. Abbo and H. M. Khudhur, New A hybrid conjugate gradient Fletcher-Reeves and Polak-Ribiere algorithm for unconstrained optimization, Tikrit J. Pure Sci., 21(1) 2015, 124-129.
- H. N. Jabbar, K. K. Abbo, and H. M. Khudhur, “Four--term conjugate gradient (CG) method based on pure conjugacy condition for unconstrained optimization,” Kirkuk Univ. J. Sci. Stud., 13(2) 2018, 101–113.
- K. K. Abbo and H. M. Khudhur, New A hybrid Hestenes-Stiefel and Dai-Yuan conjugate gradient algorithms for unconstrained optimization, Tikrit J. Pure Sci., 21(1) 2015, 118–123.
- Z. M. Abdullah, M. Hameed, M. K. Hisham, and M. A. Khaleel, Modified new conjugate gradient method for Unconstrained Optimization, Tikrit J. Pure Sci., 24(5) 2019, 86–90.
- B. Y. Al-Khayat, Introduction to Mathematical Modeling Using MATLAB, Dar Ibn Al-Atheer for Printing and Publication University of Mosul, Mosul, 2012.
Developing a New Optimization Algorithm to Predict the Risk of Car Accidents Due to Drinking Alcoholic Drinks by Using Feed-Forward Artificial Neural Networks
Yıl 2021,
Cilt: 4 Sayı: 1, 11 - 18, 03.01.2022
Alla Saad
,
Hisham Mohammed
Öz
In this research, we have developed a new algorithm in the field of optimiza-tion and its application in teaching artificial neural networks with front feeding to predict the risk of car accidents due to consuming alcoholic beverages, and the algorithm has proven a high efficiency in prediction as it was compared with the results of the model predicting the risk of car accidents due to eating Given alco-hol and the results were very close to the true solution to the model
Kaynakça
- K. Abbo and M. S Jaborry, Learning rate for the back propagation algorithm based on modified scant equation, Iraqi J. Stat. Sci., 14(26) 2014, 1–11.
- Y. A. Laylani, K. K. Abbo, and H. M. Khudhur, Training feed forward neural network with modified Fletcher-Reeves method, Journal of Multidisciplinary Modeling and Optimization, 1(1) 2018, 14–22.
- A. Antoniou and W.-S. Lu, Practical Optimization: Algorithms and Engineering Applications. Springer Science & Business Media, 2007.
- J. Nocedal and S. Wright, Numerical Optimization. Springer Science & Business Media, 2006.
- E. Polak and G. Ribiere, “Note sur la convergence de méthodes de directions conjuguées,” ESAIM Math. Model. Numer. Anal. Mathématique Anal. Numérique, 3(R1) 1969, 35-43.
- M. R. Hestenes and E. Stiefel, Methods of conjugate gradients for solving linear systems, J. Res. Nat. Bur. Stand.,49 (1) 1952, 409-436.
- R. Fletcher and C. M. Reeves, Function minimization by conjugate gradients, Comput. J., 7(2) 1964, 149-154.
- Y. H. Dai and Y. Yuan, A nonlinear conjugate gradient method with a strong global convergence property, SIAM J. Optim., 10(1) 1999, 177-182.
- L. C. W. Dixon, Conjugate gradient algorithms: quadratic termination without linear searches, IMA J. Appl. Math., 15(1) 1975, 9-18.
- K. K. Abbo and H. M. Khudhur, New A hybrid conjugate gradient Fletcher-Reeves and Polak-Ribiere algorithm for unconstrained optimization, Tikrit J. Pure Sci., 21(1) 2015, 124-129.
- H. N. Jabbar, K. K. Abbo, and H. M. Khudhur, “Four--term conjugate gradient (CG) method based on pure conjugacy condition for unconstrained optimization,” Kirkuk Univ. J. Sci. Stud., 13(2) 2018, 101–113.
- K. K. Abbo and H. M. Khudhur, New A hybrid Hestenes-Stiefel and Dai-Yuan conjugate gradient algorithms for unconstrained optimization, Tikrit J. Pure Sci., 21(1) 2015, 118–123.
- Z. M. Abdullah, M. Hameed, M. K. Hisham, and M. A. Khaleel, Modified new conjugate gradient method for Unconstrained Optimization, Tikrit J. Pure Sci., 24(5) 2019, 86–90.
- B. Y. Al-Khayat, Introduction to Mathematical Modeling Using MATLAB, Dar Ibn Al-Atheer for Printing and Publication University of Mosul, Mosul, 2012.