Search Results - (( (structures OR structural) network training algorithm ) OR ( java application using algorithm ))

A speech recognition system based on structure equivalent fuzzy neural network trained by firefly algorithm by Tahereh Hassanzadeh, Karim Faez, Golnaz Seyfi

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Backpropagation neural network training algorithm analysis / Shahrul Azmi Rosli by Rosli, Shahrul Azmi

“…This paper presents the analysis of Backpropagation Neural Network Training Algorithms in Artificial Neural Network (ANN) using MATLAB and demonstrates the analysis of training algorithms using the dataset of concrete compressive strength.…”
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Multidimensional Minimization Training Algorithms for Steam Boiler Drum Level Trip Using Artificial Intelligence Monitoring System by Ismail, F. B., Al-Kayiem, Hussain H.

“…Results are obtained from one hidden layer neural network and two hidden layers neural network structures, for both adopted algorithms. …”
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Dynamic modelling of a flexible beam structure using feedforward neural networks for active vibration control by Tuan Abdul Rahman, Tuan Ahmad Zahidi, As'arry, Azizan, Abdul Jalil, Nawal Aswan, Raja Ahmad, Raja Mohd Kamil

“…The performance of modified SFS algorithm to train a nonlinear auto-regressive exogenous model (NARX) structure FNNs-based model of the system was then compared with its predecessor and with several well-known metaheuristic algorithms. …”
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PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM by ABDALLA, OSMAN AHMED

“…An artificial neural network (ANN), or shortly "neural network" (NN), is a powerful mathematical or computational model that is inspired by the structure and/or functional characteristics of biological neural networks. …”
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Multi objective genetic algorithm for training three term backpropagation network by Osman Ibrahim, Ashraf, Shamsuddin, Siti Mariyam, Ahmad, Nor Bahiah, Qasem, Sultan Noman

“…Multi Objective Evolutionary Algorithms has been applied for learning problem in Artificial Neural Networks to improve the generalization of the training and testing unseen data.This paper proposes the simultaneous optimization method for training Three Term Back Propagation Network (TTBPN) learning using Multi Objective Genetic Algorithm.The Non-dominated Sorting Genetic Algorithm II is applied to optimize the TTBPN structure by simultaneously reducing the error and complexity in terms of number of hidden nodes of the network for better accuracy in classification problem.This methodology is applied in two kinds of multiclasses data set obtained from the University of California at Irvine repository.The results obtained for training and testing on the datasets illustrate less network error and better classification accuracy, besides having simple architecture for the TTBPN.…”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…One form of ANNs models are widely used for various applications are Feedforward Neural Networks (FFNN). The performance of ANNs depend on many factors, including the network structure, the selection of activation function, the learning rate of the training algorithm, and initial synaptic weight values, the number of input variables, and the number of units in the hidden layer. …”
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Multi-objective Hybrid Election Algorithm For Random K Satisfiability In Discrete Hopfield Neural Network by Karim, Syed Anayet

“…Moreover, the optimal performance of Random k Satisfiability logic can be achieved by applying an efficient algorithm during the training phase of Discrete Hopfield Neural Network. …”
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River Suspended Sediment Prediction Using Various Multilayer Perceptron Neural Network Training Algorithms—A Case Study in Malaysia by Mustafa, M.R., Rezaur, R.B., Saiedi, Saied, Isa, M.H.

“…It was concluded that both training algorithms SCG and LM could be recommended for suspended sediment prediction using MLP networks. …”
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Hybridised Network of Fuzzy Logic and a Genetic Algorithm in Solving 3-Satisfiability Hopfield Neural Networks by Farah Liyana, Azizan, Saratha, Sathasivam, Majid Khan, Majahar Ali, Nurshazneem, Roslan, Caicai, Feng

“…This work proposed a new hybridised network of 3-Satisfiability structures that widens the search space and improves the effectiveness of the Hopfield network by utilising fuzzy logic and a metaheuristic algorithm. …”
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An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction by Shah, Habib

“…Most of the training algorithms focus on weight values, activation functions, and network structures for providing optimal outputs. …”
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Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

“…In other words, the implemented bat algorithm in neural network structure is to get global optimization in order to minimize mean absolute percentage error, MAPE. …”
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Real-time identification of an unmanned quadcopter flight dynamics using fully tuned radial basis function network by Pairan, Mohammad Fahmi

“…The prediction performance of the proposed fully tuned RBF was compared with Multilayer Perceptron (MLP), Hybrid Multilayer Perceptron (HMLP) and RBF networks trained with CT algorithm. The findings indicated that the fully tuned RBF with minimal resource allocating networks (MRAN) automatically selected seven neurons with 9.5177 % prediction accuracy and 5.89ms mean training time. …”
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Toxic Gas Dispersion Model Based On Neural Pattern Recognition Networks by Roslan, Nurfarah Arina

“…Following the best selection of neural network algorithm, BR algorithm is further trained using 50-70% training with 10-28 hidden neurons. …”
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Binary Artificial Bee Colony Optimization For Weighted Random 2 Satisfiability In Discrete Hopfield Neural Network by Muhammad Sidik, Siti Syatirah

“…Then, the Election algorithm will be utilized to obtain a satisfied interpretation of the correct logical structure in the training phase of the Discrete Hopfield Neural Network. …”
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Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

“…In other words, the implemented bat algorithm in neural network structure is to get global optimization in order to minimize mean absolute percentage error, MAPE. …”
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Buckling Prediction in Steel Columns: Unveiling Insights with Artificial Neural Networks by Hakim, S. J. S, Paknahad, M., Kamarudin, A. F., Ravanfar, S. A., Mokhatar, S. N.

“…In this research, the behavior of steel columns under various loading conditions using Finite Element (FE) is simulated, a large amount of data for training ANNs have been generated, and multiple ANNs are trained using various architectures and training algorithms. …”
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Optimization of neural network architecture using genetic algorithm for load forecasting by Islam, B.U., Baharudin, Z., Raza, M.Q., Nallagownden, P.

“…The network structures are normally selected on the basis of the developer's prior knowledge or hit and trial approach is used for this purpose. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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Review of deep convolution neural network in image classification by Al-Saffar, Ahmed Ali Mohammed, Tao, Hai, Mohammed, Ahmed Talab

“…Then, the research status and development trend of convolution neural network model based on deep learning in image classification are reviewed, which is mainly introduced from the aspects of typical network structure construction, training method and performance. …”
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