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21 results for “gradient descent”
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Research ArticleOpen accessIn the keywordsCerebrovascular Accident Attack Classification Using Multilayer Feed Forward Artificial Neural Network with Back Propagation ErrorOlatubosun Olabode, Bola Titilayo OlabodeProblem statement: Most important problems of medical diagnosis. When there is a cerebrovascular accident attach the chances of a successful treatment depends essentially on the early diagnosis. In practice the part of medical errors while diagnosing a stroke type comes to 20-45% even for experienced doctors and the scope of methods of neurovisualization at stroke diagnosis are limited. Approach: In … …Journal of Computer Science, Vol. 8, Issue 1 · 26 Oct 2011 · 7,330 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 abstractEnhancing Dam Safety and Management: Long Short-Term Memory Based Predictive Models for Accurate Alert ForecastingNisha C. M, N. ThangarasuDam management and early alert systems are critical for effective water resource management. Accurate prediction of dam alert signals facilitates proactive decision-making, thereby aiding in the effective management and reduction of potential risks linked to dam operations. Within this research, Long Short-Term Memory (LSTM) networks are utilized to forecast dam alert signals issued from the dam by leveraging daily parameters, … …Journal of Computer Science, Vol. 22, Issue 1 · 6 Feb 2026 · 1,626 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 abstractDevelopment of Big Data Classifier for Biomedicine Early Diagnosis: An Experimental Approach Using Machine Learning MethodsMa Beth Solas Concepcion, Bobby Dioquino Gerardo, Frank Ibañez Elijorde et al.In the fast-phase world, data availability is abundant due to a rapid adaptation increase of big data technologies. Large amounts of data have been generated and collected at an unprecedented speed and scale, introducing a revolution in medical research practices for biomedicine informatics. Thus, there is an immense demand for statistically rigorous approaches, especially in the medical diagnosis discipline. Therefore, … …Journal of Computer Science, Vol. 20, Issue 4 · 1 Feb 2024 · 5,510 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting of Multistep Multivariate Financial Data Through GSO Algorithm Infused Vanilla LSTM ModelNikhitha Pai, Ilango Velchamy, Nithya B RameshPredicting time series in the financial domain requires using models that can do sequence processing tasks. One such model is the LSTM model which belongs to the family of deep learning networks. The performance measure of LSTM in a regression task is to bring down the error in the predicted values. In this study, a novel fused LSTM model integrating … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 6,074 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
Research ArticleOpen accessIn the abstractImproved Coupled Tank Liquid Levels System Based on Swarm Adaptive Tuning of Hybrid Proportional-Integral Neural Network ControllerM.S. Ramli, RM.T. Raja Ismail, M.A. Ahmad et al.Problem statement: Accuracy and stability of many systems in chemical and process industries which has Two-Input Two-Output (TITO) is one of the key factors of process which have cross coupling between process input and output. Approach: Unlike traditional neural network weight adaptation using gradient descent method, Particles Swarm Optimization (PSO) technique was utilized for adaptive tuning of neural network weights … …American Journal of Engineering and Applied Sciences, Vol. 2, Issue 4 · 31 Dec 2009 · 7,822 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Modified Conjugate Gradient Formula for Back Propagation Neural Network AlgorithmAbbas Y. Al Bayati, Najmaddin A. Sulaiman, Gulnar W. SadiqProblem statement: The Conjugate Gradient (CG) algorithm which usually used for solving nonlinear functions is presented and is combined with the modified Back Propagation (BP) algorithm yielding a new fast training multilayer algorithm. Approach: This study consisted of determination of new search directions by exploiting the information calculated by gradient descent as well as the previous search direction. The proposed … …Journal of Computer Science, Vol. 5, Issue 11 · 30 Dec 2009 · 6,989 accessesView PDFCite