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15 results for “Gradient descent method”
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Research ArticleOpen accessEvery word in the titleSufficient Descent Condition of the Polak-Ribière-Polyak (PRP) Conjugate Gradient Method without Line SearchAbdelrahman A., KH. I. Osman, Osman O.O. Yousif et al.Nonlinear conjugate gradient methods for unconstrained optimization problems are used in many aspects of theoretical and applied sciences. They are iterative methods, so at any iteration a step length is computed using a method called line search. In most cases, the sufficient descent condition plays an important role to prove the global convergence of a conjugate gradient method. Due to … …Journal of Mathematics and Statistics, Vol. 18, Issue 1 · 14 Mar 2022 · 6,360 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSelf-Generation ART-1 Neural Network with Gradient-Descent Method Aid for Latin Alphabet RecognitionMbaïtiga ZacharieProblem statement: In this study a self-generation ART-1 neural network that is an efficient algorithm that emulates the self-organizing pattern recognition developed to avoid the stability-plasticity dilemma in competitive networks learning, is presented for Latin alphabet recognition to use in a vision system for road sings recognition. Approach: The first step of our approach deals with the training process where … …Journal of Computer Science, Vol. 4, Issue 8 · 31 Aug 2008 · 6,566 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Developed Version of Conjugate Gradient Method With a New Parameter for Dai-Liao Conjugacy Condition With an Application to Solar PanelAhmad Alhawarat, Ramadan Sabra, Mehiddin Al-Baali et al.Conjugate Gradient (CG) methods are broadly employed in solving bigger-scale unconstrained optimization problems. Two famous methods are the Hestenes–Stiefel (HS) as well as Polak–Ribière–Polyak (PRP) CG methods, which usually work well in practice. However, they cannot satisfy the Global Convergence (GC) property. To retain and enhance the previous practical behavior as well as rectify the latter difficulty, this paper constructs … …Journal of Computer Science, Vol. 21, Issue 7 · 15 Jul 2025 · 3,147 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Robust Modification of Hestenes–Stiefel Conjugate Gradient Method with Strong Wolfe Line SearchAwad Abdelrahman, Osman O.O. Yousif, Khalid I. OsmanNonlinear Conjugate Gradient (CG) methods are extensively used for solving large-scale unconstrained optimization problems. Numerous of studies constructed scales and modifications have been conducted recently to improve (CG) methods. In this paper, a simple modified by its conjugate gradient method was proposed. In addition to, established global convergence property and sufficient descent condition, under Strong Wolfe line search. Numerical result … …Journal of Mathematics and Statistics, Vol. 16, Issue 1 · 14 May 2020 · 6,743 accessesView PDFCite
Research ArticleOpen accessIn the keywordsRule Extraction from Radial Basis Functional Neural Networks by Using Particle Swarm OptimizationM. R. Senapati, I. Vijaya, P. K. DashRadial basis functional neural networks (RBFNN) provide an outstanding possibility for generating rules for solving pattern classification problems. One of the most important factors in RBFNN is finding out the center and spread. This paper examines rules extracted from RBF networks trained by Particle swarm Optimization (PSO). The selection of the RBFNN centers, spreads and the network weights can be … …Journal of Computer Science, Vol. 3, Issue 8 · 31 Aug 2007 · 6,784 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Rainfall Forecasting Using Sequential Momentum-Based Artificial Neural Networks for Urban Flood ManagementSherin K K, G. SuganthiUrban floods cause severe disruption in densely populated cities and damage essential public infrastructure. Rapid urbanization and weak drainage systems further increase the risk during heavy rainfall. Accurate short-term rainfall forecasting is required to support early warning and reduce losses. This research focuses on improving rainfall prediction accuracy using an Artificial Neural Network trained with a new optimizer named Sequential … …Journal of Computer Science, Vol. 22, Issue 4 · 9 Apr 2026 · 1,539 accessesView PDFCite
Research ArticleOpen accessIn the abstractStroke Risk Assessment with Classical ML MethodsMohammad Aref Alshraideh, Najwan Alshraideh, Abedalrahman Alshraideh et al.Stroke, often caused by a disruption in the supply of essential oxygen, blood, and nutrients to the brain, represents a significant global health challenge. Due to limited resources, developing countries like Ethiopia face unique obstacles in identifying and treating strokes. This study explores the potential of Machine Learning (ML) techniques to predict stroke risk and facilitate early detection and intervention. … …Journal of Computer Science, Vol. 21, Issue 1 · 18 Dec 2024 · 4,649 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Method for Fast and Robust Intensity Based 2D/3D Registration in Differentiable FrameworkAgung Alfiansyah, Izzati Muhimmah, Arif Sasongko et al.This study introduces an innovative intensity-based registration method designed to align 3D image data volumes, such as Computed Tomography (CT), with 2D data, such as X-ray images, a crucial component of intra-operative navigation in image-guided surgery. Leveraging advanced autodifferentiable reconstruction techniques based on the GPU-accelerated Siddon algorithm, the proposed approach facilitates the generation of differentiable Digitally Reconstructed Radiographs (DRRs), enabling … …Journal of Computer Science, Vol. 20, Issue 12 · 24 Oct 2024 · 4,820 accessesView PDFCite
Research ArticleOpen accessIn the abstractA New Spectral Conjugate Gradient Method for Nonlinear Unconstrained OptimizationIbtisam A. Masmali, Zabidin Salleh, Ahmad AlhawaratTheconjugate gradient method is widely used to solve large scale unconstrainedoptimization problems. However, the rate of convergence conjugate gradient method is linearunless it restarted. In this study, we present a new spectral conjugategradient modification formula with restart property obtains the globalconvergence and descent properties.In addition, we proposed a new restart condition for Fletcher-Reeves conjugate gradient formula. The numerical resultsdemonstrated that … …Journal of Computer Science, Vol. 17, Issue 6 · 5 Jul 2021 · 6,653 accessesView PDFCite
Research ArticleOpen accessIn the abstractConjugate Gradient ‎Method: A Developed Version to Resolve Unconstrained Optimization ProblemsAhmad Alhawarat, Nguyen-Thoi Trung, Zabidin SallehOne of the important methods that are widely utilized to resolve ‎unconstrained ‎optimization problems is the Conjugate Gradient (CG) method. This paper aims to propose a new version of the CG method on the basis of Weak Wolfe-Powell (WWP) line search. The assumption is bounded below optimization problems with the Lipschitz continuous gradient. The new parameter obtains global convergence properties … …Journal of Computer Science, Vol. 16, Issue 9 · 18 Sep 2020 · 6,887 accessesView PDFCite