18 results for “Feed forward Neural Networks”

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Research ArticleOpen accessIn the abstractFunctional Link Artificial Neural Network for Classification Task in Data MiningB. B. Misra, S. DehuriIn solving classification task of data mining, the traditional algorithm such as multi-layer perceptron takes longer time to optimize the weight vectors. At the same time, the complexity of the network increases as the number of layers increases. In this study, we have used Functional Link Artificial Neural Networks (FLANN) for the task of classification. In contrast to multiple layer … …Journal of Computer Science, Vol. 3, Issue 12 · 31 Dec 2007 · 60,801 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordCascade-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 · 5,646 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordComparison 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 · 6,469 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordComparison 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 · 7,869 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordOptimization and Prediction of Motorcycle Injection System Performance with Feed-Forward Back-Propagation Method Artificial Neural Network (ANN)La Ode Ichlas Syahrullah, Nazaruddin SinagaThis research studied the use of Artificial Neural Network (ANN) using feed-forward back-propagation model to optimize and predict the performance of a motorcycle fuel injection systems of gasoline. The parameters such as speed, throttle position, ignition timing and injection timing is used as the input parameters. While the parameters of fuel consumption and engine torque is used as the output … …American Journal of Engineering and Applied Sciences, Vol. 9, Issue 2 · 16 Feb 2016 · 13,789 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordHALF OF THRESHOLD ALGORITHM: AN ENHANCED LINEAR ADAPTIVE SKIPPING TRAINING ALGORITHM OR MULTILAYER FEEDFORWARD NEURAL NETWORKSManjula Devi Ramasamy, Kuppuswami Subbaraya GounderMultilayer Feed Forward Neural Network (MFNN) has been successfully administered architectures for solving a wide range of supervised pattern recognition tasks. The most problematic task of MFNN is training phase which consumes very long training time on very huge training datasets. An enhanced linear adaptive skipping training algorithm for MFNN called Half of Threshold (HOT) is proposed in this research … …American Journal of Applied Sciences, Vol. 11, Issue 1 · 22 Nov 2013 · 7,020 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordArtificial Neural Networks Based Red Palm Weevil (Rynchophorus Ferrugineous, Olivier) Recognition SystemSaleh Mufleh Al-Saqer, Ghulam Mubashar HassanProblem statement: The most dangerous insect for the existence of palm trees in entire world is Red Palm Weevil (scientifically named as Rynchophorus Ferrugineous, Oliveir). The proposed research is conducted to develop an identification system for Automated Wireless Red Palm Weevil Detection and exterminated. The core idea of the proposed research is to develop software that can utilize image processing … …American Journal of Agricultural and Biological Sciences, Vol. 6, Issue 3 · 4 Aug 2011 · 9,190 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordOn 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 · 7,520 accessesView PDF Cite