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21 articles for “gradient descent”
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Research ArticleOpen accessPhrase in the titleConvolution Neural Networks of Dynamically Sized Filters with Modified Stochastic Gradient Descent Optimizer for Sound ClassificationManu Pratap Singh, Pratibha RashmiDeep Neural Networks (DNNs), specifically Convolution Neural Networks (CNNs) are found well suited to address the problem of sound classification due to their ability to capture the pattern of time and frequency domain. Mostly the convolutional neural networks are trained and tested with time-frequency patches of sound samples in the form of 2D pattern vectors. Generally, existing pre-trained convolutional neural … …Journal of Computer Science, Vol. 20, Issue 1 · 13 Dec 2023 · 5,781 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleGradient Descent Learning for Utility Current Compensation using Active Regenerative PWM FilterR. Balamurugan, G. GurusamyProblem statement: Harmonic analysis is a primary matter of power quality assessment. Its main intention is to check the utility whether it is delivering the loads without any deviations in voltages and currents. The problem is due to proliferation of Electronic converters and power electronics which gave birth to numerous new applications, offering unmatched comfort to the customers. Approach: Harmonics … …Journal of Computer Science, Vol. 7, Issue 12 · 14 Oct 2011 · 6,545 accessesView PDFCite
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 titleNew Scaled Sufficient Descent Conjugate Gradient Algorithm for Solving Unconstraint Optimization ProblemsAbbas Y. AL-Bayati, Rafiq S. MuhammadProblem statement: The scaled hybrid Conjugate Gradient (CG) algorithm which usually used for solving non-linear functions was presented and was compared with two standard well-Known NAG routines, yielding a new fast comparable algorithm. Approach: We proposed, a new hybrid technique based on the combination of two well-known scaled (CG) formulas for the quadratic model in unconstrained optimization using exact line … …Journal of Computer Science, Vol. 6, Issue 5 · 31 May 2010 · 7,046 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 keywordsEfficient 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 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 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 keywordsSupervised Machine Learning Model-Based Approach for Performance Prediction of StudentsAbdul Razaque, Abrar M. AlajlanPredicting students’ performance is one of the crucial issue for learning contexts, since it helps to develop alternative recommendation systems for academically weak students. Thus, several methods and practices have been applied for educational improvement. However, most of the existing methods do not determine the performance of the students. In this study, we have studied the execution of six machine … …Journal of Computer Science, Vol. 16, Issue 8 · 28 Aug 2020 · 7,082 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