A New Conjugate Gradient Method for Learning Fuzzy Neural Networks

Autor: MOHAMMED, Hisham, ABBO, Khalil K.

Publikováno v: Journal of Multidisciplinary Modeling and Optimization, Vol 3, Iss 2, Pp 57-69 (2021)
Volume: 3, Issue: 2 57-69
Journal of Multidisciplinary Modeling and Optimization

In this paper, we suggest a conjugate gradient method, which belongs to the op-timization methods for learning a fuzzy neural network model that is based on Takagi Sugeno. Where we developed a new algorithm based on the Polak–Ribière–Polak (PRP)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::657fb328851efdab52324c48279f3f38
https://dergipark.org.tr/tr/pub/jmmo/issue/60925/852212

Training Feedforward Neural Networks to Predict the Size of the Population by Using a New Hybrid Method Hestenes-Stiefel (HS) and Dai-Yuan (DY)

Autor: MOHAMMED, Hisham, ABBO, Khalil K., KHUDHUR, Aydin

Publikováno v: Volume: 2, Issue: 2 69-78
Journal of Soft Computing and Artificial Intelligence

We proposed a new conjugate gradient type hybrid approach in this study, which is based on merging Hestenes-Stiefel and Dai-Yuan algorithms using the spectral direction conjugate algorithm, we showed their absolute convergence. Under some assumptions

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=tubitakulakb::3b05a1f415ef19ddbf4b912538022824
https://dergipark.org.tr/tr/pub/jscai/issue/66233/957309

Training feed forward neural network with modified Fletcher-Reeves method

Autor: LAYLANİ, Yoksal A., ABBO, Khalil K., KHUDHUR, Hisham M.

Publikováno v: Journal of Multidisciplinary Modeling and Optimization, Vol 1, Iss 1, Pp 14-22 (2018)
Volume: 1, Issue: 1 14-22
Journal of Multidisciplinary Modeling and Optimization

In this research, a modified Fletcher-Reeves (FR) conjugate gradient algorithm for training large scale feed forward neural network (FFNN) is presented. Under mild conditions, we establish that the proposed method satisfies the sufficient descent con

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::24fa24a778344cce66de37db801d422a
https://dergipark.org.tr/tr/pub/jmmo/issue/38716/392124?publisher=http-w3-sdu-edu-tr-personel-00606-prof-dr-ahmet-sahiner

A hybridization of the Hestenes-Stiefel and Dai-Yuan Conjugate Gradient Methods.

Autor: Laylani, Yoksal A.¹ yuksel@uokirkuk.edu.iq, Khudhur, Hisham M.² hisham892020@uomosul.edu.iq, Nori, Edrees M.² edreesnori@uomosul.edu.iq, Abbo, Khalil K.³ dr.khalil-khuder@uotelafer.edu.iq

Publikováno v: European Journal of Pure & Applied Mathematics. Apr2023, Vol. 16 Issue 2, p1059-1067. 9p.