Search Results - (( basic learning module algorithm ) OR ( java implementation swarm algorithm ))
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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Interactive learning package for artificial neural network (Demonstration Module) / Camellia Mohd Kamal
Published 2004“…Interactive Learning Package for Artificial Neural Network (Demonstration Module) is a learning package that allow the users to learn and enhance the understanding of the ANN subject in more detailed way and apply in the demonstration parts. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Simulation of Orthogonal Frequency Division Multiplexing (OFDM) signaling
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Surface Normals with Modular Approach and Weighted Voting Scheme in 3D Facial Expression Classification
Published 2014“…A modular approach is employed where a face is decomposed into six different regions and the expression classification for each module is carried out independently. We constructed a Weighted Voting Scheme (WVS) to infer the emotion underlying a collection of modules using a weight that is determined using the AdaBoost learning algorithm. …”
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Sensorless induction motor speed control for electric vehicles using enhanced hybrid flux estimator with ann-ifoc controller
Published 2022“…The function of the ANN was to improve speed-tracking performance, and the learning rate of the ANN inside the indirect FOC’s structure trained using the Levenberg-Marquardt (LM) algorithm was varied in order to increase speed-tracking accuracy when combined with the improved ANN speed controller. …”
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Incremental learning for large-scale stream data and its application to cybersecurity
Published 2015“…To process large-scale data sequences, it is important to choose a suitable learning algorithm that is capable to learn in real time. …”
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