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175 articles for “Gradient”
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Research ArticleOpen accessEvery word in the titleRandom Forest and Extreme Gradient Boosting with Bayesian Hyperparameter Optimization for Landslide Susceptibility Mapping in Penang Island, MalaysiaDorothy Anak Martin Atok, Soo See Chai, Kok Luong Goh et al.Landslide susceptibility models often face challenges of overfitting and overestimation. This research focuses on improving the predictive capabilities of the Extreme Gradient Boosting (XGBoost) and Random Forest (RF) algorithms by applying Bayesian Hyperparameter Optimization (BayesOpt). Penang Island, a region in Malaysia prone to frequent landslides, was chosen as the study area. Ten Landslide Conditioning Factors (LCFs), including elevation, slope angle, … …Journal of Computer Science, Vol. 21, Issue 10 · 16 Dec 2025 · 3,103 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA 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 accessEvery word in the titleSentiment Analysis Using Light Weight - Gradient Boosting Machine based Feature SelectionBikku Ramavath, Srikanth Kadainti, Nemani SubashSentiment analysis is a significant task in Natural Language Processing (NLP) that differentiates the emotions and opinions expressed in text or reviews. The sentiment analysis is challenging due to the complex language patterns and inappropriate or redundant features used for classification. In this research, the Light Weight - Gradient Boosting Machine (LWGBM) based feature selection is proposed to choose relevant … …Journal of Computer Science, Vol. 21, Issue 5 · 26 May 2025 · 4,695 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleGradient Boosting for Heart Stroke Prediction: Investigating Unexpected Risk FactorsAniket Kailas Shahade, Priyanka V. DeshmukhHeart stroke prediction is a critical area in healthcare, aiming to identify individuals at risk and provide timely intervention. This research leverages machine learning algorithms, including Decision Tree, Random Forest, AdaBoost, and Gradient Boost, to predict the likelihood of stroke, with Gradient Boosting delivering the most accurate results. Our analysis uncovers intriguing and unexpected relationships between stroke risk and various … …Journal of Computer Science, Vol. 21, Issue 1 · 16 Dec 2024 · 4,939 accessesView PDFCite
Research ArticleOpen accessEvery word 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 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 titleA 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 accessEvery word in the titleFirst-Degree Polynomial Gradient Approach to Reveal the Severity of COVID-19 Pandemic in Affected CountriesDedy Rahman Wijaya, Anak Agung Gde Agung, Tora Fahrudin, SuryatiningsihCOVID-19 is a new type of Coronavirus (2019-nCoV) which originated from Wuhan in China. Since 11 March 2020, WHO has declared COVID-19 as a pandemic. Currently, it has spread to 175 countries or regions around the world. From day to day, confirmed, recovered and death cases have been reported. This data rapidly changes that indicates an uncertain situation. This uncertain … …Journal of Computer Science, Vol. 17, Issue 2 · 16 Mar 2021 · 7,171 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleConjugate 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
Research ArticleOpen accessEvery word in the titleA 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