Search Results - (( using neural problem algorithm ) OR ( java application customization algorithm ))

The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement by Hosseini E., Al-Ghaili A.M., Kadir D.H., Daneshfar F., Gunasekaran S.S., Deveci M.

“…SGA is used in the process of solving optimization test problems by neural networks. …”

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

“…Backpropagation, or propagation of error, is a common method of teaching artificial neural networks how to perform a given task. There is several training algorithm that can be used to compute a neural network problem. …”
Get full text
Get full text

Studying the effect of training Levenberg Marquardt neural network by using hybrid meta-heuristic algorithms by Abubakar, Adamu, Khan, Abdullah, Nawi, Nazri Mohd, Rehman, M. Z., Teh , Ying Wah, Chiroma , Haruna, Herawan, Tutut

Get full text
Get full text
Get full text
Get full text

Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

“…Backpropagation (BP) algorithm is widely used to solve many real world problems by using the concept of Multilayer Perceptron (MLP). …”
Get full text
Get full text

Neural networks optimization through genetic algorithm searches: A review by Chiroma, Haruna, Mohd Nor, Ahmad Shukri, Abdul Kareem, Sameem, Abubakar, Adamu, Hermawan, Arief, Qin, Hongwu, Hamza, Mukhtar Fatihu, Herawan, Tutut

“…We provide an analysis and synthesis of the research published in this area according to the application domain, neural network design issues using genetic algorithms, types of neural networks and optimal values of genetic algorithm operators (population size, crossover rate and mutation rate). …”
Get full text
Get full text
Get full text
Get full text

Studying the Effect of Training Levenberg Marquardt Neural Network by Using Hybrid Meta-Heuristic Algorithms by Abubakar, A., Khan, A., Nawi, N.M., Rehman, M.Z., Teh, Y.W., Chiroma, H., Herawan, T.

Get full text
Get full text

Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification by Nuaimi, Zakaria Noor Aldeen Mahmood Al, Abdullah, Rosni

“…By optimizing the training of the neural networks using optimal weight set, better results can be obtained by the neural networks. …”
Get full text
Get full text
Get full text

An Improvement on Extended Kalman Filter for Neural Network Training by Tsan, Ken Yim

“…This study explored the training of a neural network inference system using the extended Kalman filter (EKF) learning algorithm. …”
Get full text
Get full text

Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification by Al Nuaimi, Zakaria Noor Aldeen Mahmood, Abdullah, Rosni

“…By optimizing the training of the neural networks using optimal weight set, better results can be obtained by the neural networks.Traditional neural networks algorithms such as Back Propagation (BP) were used for ANNT, but they have some drawbacks such as computational complexity and getting trapped in the local minima.Therefore, evolutionary algorithms like the Swarm Intelligence (SI) algorithms have been employed in ANNT to overcome such issues.Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
Get full text
Get full text
Get full text

Static hand gesture recognition using artificial neural network / Haitham Sabah Hasan by Hasan, Haitham Sabah

“…Artificial neural network is built for the purpose of classification by using the back- propagation learning algorithm. …”
Get full text
Get full text

Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman by Seman, Noraini

“…A variety of automatic knowledge acquisition or learning and adaptation concepts need to be established in speech recognition using AI approaches. These key concepts can only be implemented using artificial neural networks (ANNs) approach. …”
Get full text
Get full text

Case study : an effect of noise in character recognition system using neural network by Mohamad, Esmawaty

“…Neural networks are useful tools for solving many type of problems. …”
Get full text
Get full text

BAT-BP: A new BAT based back-propagation algorithm for efficient data classification by Mohd. Nawi, Nazri, M. Z., Rehman, Hafifi, Nurfarian, Khan, Abdullah, Siming, Insaf Ali

“…Thus, this study investigates the use of Bat algorithm along with back-propagation neural network (BPNN) algorithm in-order to gain optimal weights to solve the local minima problem and also to enhance the convergence rate. …”
Get full text
Get full text

Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification by Nawi, N.M., Khan, A., Rehman, M.Z., Chiroma, H., Herawan, T.

“…The proposed CSERN and CSBPERN algorithms are compared with artificial bee colony using BP algorithm and other hybrid variants algorithms. …”
Get full text
Get full text
Get full text

Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…These algorithms have widely been used to optimize the learning mechanism of classifiers, particularly on Artificial Neural Network (ANN) Classifier. …”
Get full text
Get full text
Get full text

The advantages of genetic algorithm and neural networks to forecast air pollution trend in Malaysia: an overview / Mohamad Idham Md Razak … [et al.] by Md Razak, Mohamad Idham, Ahmad, Ismail, Bujang, Imbarine, Talib, Adi Hakim, Kedin, Nor Adila

“…Artificial neural networks may either be used to gain an understanding of biological neural networks, or for solving artificial intelligence problems without necessarily creating a model of a real biological system. …”
Get full text
Get full text

Eye Diagram Modeling Of High-Speed Channels Using Artificial Neural Networks With An Improved Adaptive Sampling Algorithm by Goay, Chan Hong

“…This reduces the number of training samples by 16.1%, validation samples by 14.7% and neural model development time by 23%. Besides that, the use of the prior knowledge input neural network (PKI-ANN) and the prior knowledge input difference neural network (PKID-ANN) for the modeling of high dimensional SI problem is proposed. …”
Get full text
Get full text

Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
Get full text
Get full text
Get full text

WCBP: A new water cycle based back propagation algorithm for data classification by Mohd. Nawi, Nazri, Khan, Abdullah, Firdaus, Naim, M. Z., Rehman, Siming, Insaf Ali

“…Therefore, this paper proposed the use of WC algorithm in combination with Back-Propagation neural network (BPNN) algorithm to solve the local minima problem in gradient descent trajectory. …”
Get full text
Get full text

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). …”
Get full text
Get full text