40 results for “Feed Forward Neural Network”

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Research ArticleOpen accessIn the keywordsForecasting River Flow in the USA: A Comparison between Auto-Regression and Neural Network Non-Parametric ModelsAbdel K.M. Baareh, Alaa F. Sheta, Khaled A. KhnaifesForecasting a time series became one of the most challenging tasks to variety of data sets. The existence of large number of parameters to be estimated and the effect of uncertainty and outliers in the measurements makes the time series modeling too complicated. Recently, Artificial Neural Network (ANN) became quite successful tool to handle time series modeling problem. This paper … …Journal of Computer Science, Vol. 2, Issue 10 · 31 Oct 2006 · 6,962 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsCascade-Based Non-Linear Feedforward Neural Networks for Bi-Directional MemoryThipendra Pal Singh, Tanupriya Choudhury, Rohini AIn today's world, efficient computation is the key to success in many fields. Pattern association plays an influential role in many areas of life, such as learning and memory. In complex dynamics, bidirectional associative memory has been effectively demonstrated by neural networks. However, these neural networks face challenges in terms of performance, such as computational time. A random bipolar input … …Journal of Computer Science, Vol. 19, Issue 4 · 28 Feb 2023 · 5,640 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsStudy of Fractional Order Integro-Differential Equations by using Chebyshev Neural NetworkSarkhosh S. Chaharborj, Shahriar S. Chaharborj, Yaghoub MahmoudiRecently fractional integro-differential equations have been proposed for the modeling of many complex systems. Simulation of these equations requires the development of suitable numerical methods. This paper is devoted to finding the numerical solution of some classes of fractional integro-differential equations by employing the Chebyshev Neural Network (ChNN). The accuracy of proposed method is shown by comparing the numerical results … …Journal of Mathematics and Statistics, Vol. 13, Issue 1 · 11 Feb 2017 · 7,403 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsA Review on Recent Research and Implementation Methodologies on Medical Image SegmentationS. K. Somasundaram, P. AlliProblem statement: Image segmentation plays a very important role in digital imaging applications for classifying the anatomical structures and other Regions of Interest. Segmentation refers to the process of identifying and isolating the surface and regions of the digital image which corresponds to the structural units. Approach: In the past few decades, many methods have been proposed to segment the … …Journal of Computer Science, Vol. 8, Issue 1 · 4 Nov 2011 · 7,117 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsFish Recognition Based on Robust Features Extraction from Size and Shape Measurements Using Neural NetworkMutasem Khalil Alsmadi, Khairuddin Bin Omar, Shahrul Azman Noah, Ibrahim AlmarashdehProblem statement: Image recognition is a challenging problem researchers had been research into this area for so long especially in the recent years, due to distortion, noise, segmentation errors, overlap and occlusion of objects in digital images. In our study, there are many fields concern with pattern recognition, for example, fingerprint verification, face recognition, iris discrimination, chromosome shape discrimination, optical … …Journal of Computer Science, Vol. 6, Issue 10 · 5 Aug 2010 · 9,299 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsOn the Application of Artificial Neural Networks in Analyzing and Classifying the Human ChromosomesIbrahiem M.M. El EmaryThis study aimed to represent an advanced software tool assists in analyzing and classifying the human chromosomes. Our new software handles both classifying and analyzing the medical image of human chromosomes according to the following steps: 1- we use the image processing utilities in Matlab to analyze the image; where we provide a new filter to remove the noise depending … …Journal of Computer Science, Vol. 2, Issue 1 · 31 Jan 2006 · 7,515 accessesView PDF Cite

Research ArticleOpen accessIn the abstractClassification of Finger Vein Image Using Convolutional Neural NetworkAhmed S. Hameed, Shawkat K. Guirguis, Hend A. ElsayedCurrently available technologies can perform rather well, but their effectiveness is mostly contingent on how well the venous images being analyzed are quality images. Finger vein features have garnered significant attention in the past few years as a potential means of automatic user identification. A significant amount of daily usage goes into the very vital personal identification procedure. The identification … …Journal of Computer Science, Vol. 21, Issue 2 · 6 Jan 2025 · 4,712 accessesView PDF Cite

Research ArticleOpen accessIn the abstractComparison of Multiple Linear Regression and Neural Network Models in Bank Performance Prediction in BotswanaHassan Kablay, Victor GumboBank performance is critical to the banking sector and the economy as a whole. In this study, Multiple Linear Regression (MLR) technique and feed forward Neural Network (NN) are used to predict the performance of 11 banks in Botswana. Return on Assets (RoA) is used as the dependent variable, while management quality, credit risk, liquidity, financial leverage and capital adequacy … …Journal of Mathematics and Statistics, Vol. 17, Issue 1 · 10 Jan 2022 · 6,465 accessesView PDF Cite

Research ArticleOpen accessIn the abstractFault-Tolerant Control of a Nonlinear Uncertain System: A Neural Network-Based Passive Approaches and Comparative Study with State-of-the-Art Control ApproachesSejal K. Raval, Himanshukumar Rajendrabhai Patel, Vipul A. ShahThis article suggests passive methods for designing Fault-Tolerant Control (FTC) for nonlinear uncertain systems with actuator and leak faults. To anticipate the Fault-Tolerant Control (FTC) action to overcome the actuator and leak faults, two-layer Feed-Forward Back-Propagation Neural Network (FFBPNN) and two-layer Cascade Forward Neural Network (CFNN) have been used, it will also tolerate external process additive disturbances. We employ the … …Journal of Computer Science, Vol. 17, Issue 7 · 3 Aug 2021 · 6,736 accessesView PDF Cite

Research ArticleOpen accessIn the abstractComparison of Linear and Non-Linear Regression Models for Non-Invasive Blood Glucose MeasurementDorsaf Ghozzi, Yassine Manai, Khaled NouriThis paper deals with a new approach of non-invasive glucose monitoring based on near infrared spectroscopy. The proposed approach is coupled with a regression analysis in order to improve the predictive capacity of the designed device. Basic spectral data is a comparison that has been established between linear and non-linear machine learning regression algorithms. The experimental results show that feed … …Journal of Computer Science, Vol. 15, Issue 11 · 13 Nov 2019 · 7,864 accessesView PDF Cite