A novel recurrent neural network for solving quadratic programming problems
عنوان مقاله: A novel recurrent neural network for solving quadratic programming problems
شناسه ملی مقاله: FJCFIS02_186
منتشر شده در دومین کنگره مشترک سیستمهای فازی و هوشمند ایران در سال 1387
شناسه ملی مقاله: FJCFIS02_186
منتشر شده در دومین کنگره مشترک سیستمهای فازی و هوشمند ایران در سال 1387
مشخصات نویسندگان مقاله:
S Effati - Payam Noor University (PNU), Quchan, Iran
M. Ranjbar
خلاصه مقاله:
S Effati - Payam Noor University (PNU), Quchan, Iran
M. Ranjbar
This paper presents a novel recurrent neural network for solving quadratic programming problems. The new model has a simple form, furthermore has a good convergence rate with a less number calculation operation than the old models. It converges very fast to exact solution of the dual problem and by substituting in a formulation, the optimal solution of the original problem is obtained. We solve neural network model with one of numerical method. Finally, simple numerical example is provided for the sake of illustration.
کلمات کلیدی: Neural network, quadratic programming, differential equation
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/203896/