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Logic Programming In Radial Basis Function Neural Networks by Hamadneh, Nawaf

“…Two techniques were developed. The first technique is to encode the logic programming in radial basis function neural networks. …”
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Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu by Sabtu, Melati

“…There are three main programs work together. The programs are back-propagation neural network program, training and performance program and recognition program. …”
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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 by Hamzah, Irni Hamiza, Ibrahim, Mohammad Nizam, Mohd Kasim, Linda

“….: CCD cameras, microphones and scanners) have fostered the development of pattern recognition algorithms in new application domains (i.e.: fuzzy logic, neural network and genetic algorithm). …”
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Prediction on heart disease using multilayer neural network / Lily Syahira Sabrina Ab Rahman by Ab Rahman, Lily Syahira Sabrina

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Flow regime identification of particles conveying in pneumatic pipeline using electric charge tomography and neural network techniques by Ahmed Sabit, Hakilo

“…A neural network based flow regime identifier program is developed in Matlab environment. …”
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The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach by Ab. Malik, Rosely, Jamil S., Mohamed

“…In this study, the developed algorithm is further expanded to include computation of the weight-matrix of a sequential associative feedback-type neural net model for the determination of service load of a single pile is introduced. …”
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Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

“…Two programs have been developed; Particle Swarm Optimization Feedforward Neural Network (PSONN) and Genetic Algorithm Backpropagation Neural Network (GANN). …”
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Neural network based model predictive control for a steel pickling process by Kittisupakorn, P., Thitiyasook, P., Hussain, Mohd Azlan, Daosud, W.

“…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

“…In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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Moving detection using cellular neural network (CNN) by Prema Latha, Subramaniam

“…This paper comprises the implementation of the basic templates available in Cellular Neural Network. The templates are programmed in MATLAB. …”
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Determining Suitable Program For SPM Holder Using Neural Network Approach by Noraisah, Sudin

“…This study involves the development of a neural network (NN) prediction model proposed for the educational spanding spesifically in determining suitable program for SPM Holder . …”
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Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus by Darus, Zamzuhairi

“…This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. A multilayer feed-forward artificial neural network (ANN) with evolution programming learning algorithm for calculation of voltage stability margins (VSM). …”
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NEUCOMP2 - parallel neural network compiler by Sulaiman, Md. Nasir, Evans, D. J.

“…Experiments were carried out to study the performance of the NEUCOMP2 programs for the backpropagation network. NEUCOMP2 was developed and run on the Sequent Balance 8000 computer system at Parallel Algorithm Research Centre, U.K.…”
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Backpropagation algorithm for rice yield prediction by Puteh, Saad, Mohamed Rizon, Mohamed Juhari, Nor Khairah, Jamaludin, Siti Sakira, Kamarudin, Aryati, Bakri, Nursalasawati, Rusli

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Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization by Lee, Jesee Kar Ming

“…Firstly, using MATLAB program, the ANN model is developed based on optimized topology and is then furthered optimized by genetic algorithm (GA) and particle swarm optimization (PSO) using MINITAB program. …”
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Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
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The development of extra axial brain tumor detection prototype using back propagation based neural network / Suriyanti Panagen by Panagen, Suriyanti

“…Knowledge appearance is compulsory for neural network in which it comes under the training phase before it recognize or detecting any pattern.A study about the artificial neural network has been done and back propagation training algorithm is suitable for this system development. …”
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Speed control of separately excited dc motor using artificial intelligent approach by Bernard, Albinus

“…These two neural are training by Levenberg�Marquardt. The effectiveness of the proposed method is verified by develop simulation model in MATLAB-Simulink program. …”
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SYSTEMATIC DESIGN OF SIMPLY STRUCTURED COMPENSATOR by FUNG , CHUN TING

“…This project aims to develop the algorithm for the tuning method that based on Nyquist Stability Criterion and at later stage build a Neural Network Model to predict the tuning parameters for the PID controller. …”
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Voltage tracking of a DC-DC buck converter using neural network control by Mohamad Narsardin, Mohamad Adhar

“…In order to overcome this main problem, a neural network controller with online learning technique based on back propagation algorithm is developed. …”
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