Search Results - (( developing learning propagation algorithm ) OR ( java implication based algorithm ))
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Face expression recognition using artificial neural network (ANN) / Mazuraini Ghani
Published 2005“…However, the performances of neural network in learning and classification task should be enhanced by redesigning and conducting experiment on other learning algorithm than back-propagation.…”
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Early detection of dengue disease using extreme learning machine
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Octane number prediction for gasoline blends using convolution neural network / Zhu Yue
Published 2021“…In the project three commonly use algorithm are used for prediction of octane number for gasoline blends, which describes the behavior of the fuel in the engine at lower temperatures and speeds, and is an attemp to simulate acceleration behavior.These tree algorithm are back propagation (BP), radial basis funtion (RBF) and Extreme learning machine (ELM) algorithm. …”
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Gender classification on skeletal remains: efficiency of metaheuristic algorithm method and optimized back propagation neural network
Published 2020“…Once the set of significant features was obtained, the learning rate and momentum of Back Propagation Neural Network (BPNN) were optimized. …”
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Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu
Published 2005“…The project used Back-propagation Neural Network for the algorithm to classified images. …”
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Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding
Published 2007“…One of the essential factors that affect the performance of Artificial Neural Networks is the learning algorithm. The performance of Multilayer Feed Forward Artificial Neural Network performance in image compression using different learning algorithms is examined in this paper. …”
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Bio-signal identification using simple growing RBF-network (OLACA)
Published 2007“…An enhanced online adaptive centre allocation algorithms (or resource allocation network (RAN)) using simple/stochastic back-propagation method with minimal weight update variant are developed for direct-link radial basis function (DRBF) networks. …”
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E-Handrawn Calculator
Published 2008“…The purpose of this project is to demonstrate an application of back-propagation network (comparison of training their algorithms and transfer function) in order to developing e-Hand-Drawn Calculator. …”
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Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques
Published 2023Conference Paper -
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Modified spectral clustering algorithm for semisupervised face annotation modeling
Published 2025“…To improve accuracy, an optimized similarity matrix was developed. It also integrated MustLink (ML) and Cannot-Link (CL) constraints, generated efficiently via the Label Propagation Algorithm (LPA) enhanced by combining Share Nearest Neighbour (SNN) and Radial Basis Function (RBF). …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm
Published 2023Conference Paper -
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Poverty Classification of Central Perak Population Using Machine Learning
Published 2019“…In this study, back propagation algorithm and other machine learning algorithm will be used to build models via anaconda using python programming language that can classify each poor household appropriate their poverty status. …”
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Final Year Project -
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Predicting the optimum compositions of a transdermal nanoemulsion system containing an extract of Clinacanthus nutans leaves (L.) for skin antiaging by artificial neural network mo...
Published 2017“…The model was applied to optimize the particle size of the transdermal nanoemulsion system containing an extract of C. nutans leaves for skin antiaging. Five universal learning algorithms—incremental back propagation, batch back propagation, quick propagation, genetic algorithm, and Levenberg-Marquardt—were used in the ANN to achieve the optimum topologies. …”
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Grid base classifier in comparison to nonparametric methods in multiclass classification
Published 2010“…The two algorithms were compared, and the proposed algorithm was found to be able to both learn and classify quickly. …”
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Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach
Published 2009“…The two algorithms were compared, and the proposed algorithm was found to be able to both learn and classify quickly. …”
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Advances of metaheuristic algorithms in training neural networks for industrial applications
Published 2023Article
