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Aplikasi rangkaian neural dalam pengesanan simpang bagi penterjemah lakaran pintar
Published 2006“…Back propagation neural network algorithm was used to develop and produce the classifier for corner detector algorithm. …”
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Toxic Gas Dispersion Model Based On Neural Pattern Recognition Networks
Published 2022“…Thus, in this study, development of deep neural network is carried out using MATLAB. …”
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A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy
Published 2022“…GDP forecasting is aided by the genetic algorithm radial basis neural network, which allows the government to make timely and effective macrocontrol plans based on the forecast trend of GDP in the region. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin
Published 2014“…As a conclusion, the MAPE obtained for the Bat Algorithm based Multi-Layer Feedforward Neural Network is 4.79 in %.…”
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Development of hybrid algorithm of residual bootstrap artificial neural network based on sukuk volatility forecast model.
Published 2018“…Development of hybrid algorithm of residual bootstrap artificial neural network based on sukuk volatility forecast model. by Nurul Hila Zainuddin…”
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Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin
Published 2014“…As a conclusion, the MAPE obtained for the Bat Algorithm based Multi-Layer Feedforward Neural Network is 4.79 in %.…”
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8
Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding
Published 2007“…Based on Gradient Descent, Conjugate Gradient, Quasi-Newton techniques three different error back propagation algorithms have been developed for use in training two types of neural networks, a single hidden layer network and three hidden layers network. …”
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The development of an automated pattern recognition based on neural network / Irni Hamiza Hamzah, Mohammad Nizam Ibrahim and Linda Mohd Kasim
Published 2006“…Based on this idea, the objective of this project is to develop an automated pattern recognition system based on neural network to recognize the pattern of loaded data file. …”
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Development of intelligent 3D solid modeler based on artificial intelligent technique
Published 2008“…The reconstruction contains two categories namely deriving depth values and deriving hidden point while the representation is the combination of neural network and mathematical model. Four contributions presented in this thesis were a new framework for solid model reconstruction and representation, a new experimental data design in development of the neural network models, neural network models for solid model reconstruction, and hybrid algorithm in representing solid model. …”
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Artificial neural network based fast edge detection algorithm for MRI medical images
Published 2017“…Therefore, the objective of this paper is to develop a fast ANN based edge detection algorithm for MRI medical images. …”
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Application Of Neural Network In Malaria Parasites Classification
Published 2006“…The first stage of this project is to develop the neural network using MATLAB Neural Network Toolbox and Borland C++ Builder. …”
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Neural network based model predictive control for a steel pickling process
Published 2009“…A multi-layer feedforward neural network model based predictive control scheme is developed for a multivariable nonlinear steel pickling process in this paper. …”
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Backpropagation neural network based on local search strategy and enhanced multi-objective evolutionary algorithm for breast cancer diagnosis
Published 2019“…However, the performance of such methods is based on the algorithms or technique. In this paper, we develop an intelligent technique using multiobjective evolutionary method hybrid with a local search approach to enhance the backpropagation neural network. …”
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Acceleration Strategies For The Backpropagation Neural Network Learning Algorithm
Published 2001“…The backpropagation algorithm has proven to be one of the most successful neural network learning algorithms. …”
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Neural Networks based fault diagnosis of ac motors
Published 2008“…The proposed ANN-based fault detector is developed using the Resilient Error Back Propagation (RPROP) training algorithm. …”
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Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza
Published 2024“…Second objective is to develop the prototype of daisy species classification based on image using CNN algorithm. …”
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Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines
Published 2008“…The developed algorithm is verified with dedicated testing data. …”
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Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques
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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. …”
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