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Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network
Published 2021“…Prior to the development of ANN-based WQI prediction model, the BR algorithm was chosen with two-, three-, four-, five- and six-neuron architectures for 60% and 70% training. …”
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Toxic Gas Dispersion Model Based On Neural Pattern Recognition Networks
Published 2022“…To achieve the objectives, two phases of structure architecture of NPR is carried out. First, NPR development is developed using three different algorithms which are Levenberg-Marquart (LM), Bayesian Regularization (BR) and Scaled Conjugated Gradient (SCG) to propose the best network algorithm using 70% training and 10-28 hidden neurons. …”
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Performance comparison of feedforward neural network training algorithms in modeling for synthesis of polycaprolactone via biopolymerization
Published 2018“…A multilayer feedforward neural network (FFNN) model with 11 different training algorithms is developed for the multivariable nonlinear biopolymerization of polycaprolactone (PCL). …”
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Slew Control of Prolate Spinners Using Single Magnetorquer
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Hybrid honey badger algorithm with artificial neural network (HBA-ANN) for website phishing detection
Published 2024“…There are multiple techniques in training the network, one of which is training with metaheuristic algorithms. …”
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Logic Programming In Radial Basis Function Neural Networks
Published 2013“…The analysis revealed that performance of particle swarm optimization algorithm and Prey predator algorithm are better to use in training the networks. …”
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Thesis -
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…Using Landsat Thematic Mapper (TM) and ModisIAster Airborne Simulator (hMSTER) images as the test datasets, the BBSI algorithm was compared to the Optimum Index Factor (OIF) algorithm in selection of the best three-band combination for image visualization. …”
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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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Development of classification algorithms of human gait
Published 2022“…Two classification algorithms were developed: Support Vector Machine (SVM) classification algorithm and Artifical Neural Network (ANN). …”
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Final Year Project / Dissertation / Thesis -
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PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM
Published 2011“…This research focuses on the use of binaryencoded genetic algorithm (GA) to implement efficient search strategies for the optimal architecture and training parameters of a multilayer feed-forward ANN. …”
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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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Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin
Published 2022“…The Windows malware dataset has been trained and tested by these three machine learning algorithms to get the percentage detection accuracy. …”
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Student Project -
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Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization
Published 2022“…The ANN model topology is designed using selection from the best training algorithm, transfer function, number of training runs (1000-5000), number of hidden layers (1-3) and nodes (5-15). …”
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Thesis -
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REDUCING LATENCY IN A VIRTUAL REALITY-BASED TRAINING APPLICATION
Published 2006“…In order to overcome latency problem, this research is an attempt to suggest a new prediction algorithm based on heuristic that could be used to develop a more effective and general system for virtual training applications. …”
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