Search Results - (( using simulation method algorithm ) OR ( parameter classifications using algorithm ))
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Simulated Kalman filter (SKF) algorithm is one of the algorithms under this classification. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Simulated Kalman filter (SKF) algorithm is one of the algorithms under this classification. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data
Published 2014“…The algorithm also utilizes certain statistical features from the EEG signal that are used as features to the classifier logic. …”
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RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm
Published 2018“…The efficiency of the proposed method is verified by means of simulation on four classification problems. …”
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Predicting noise-induced hearing loss (NIHL) in TNB workers using GDAM algorithm
Published 2012“…The traditional Back-propagation Neural Network (BPNN) is a supervised Artificial Neural Networks (ANN) algorithm. It is widely used in solving many real time problems in world. …”
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Case study : an effect of noise in character recognition system using neural network
Published 2003“…The effect of the created network with noise are seen. This projects uses the most popular training method in character recognition problem, namely backpropagation algorithm. …”
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Fault classification in smart distribution network using support vector machine
Published 2023“…Initial finding from simulation result indicates that the proposed method is quick in learning and shows good accuracy values on faults type classification in distribution system. …”
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Embedded Fuzzy Classifier for Detection and Classification of Preseizure State Using Real EEG Data
Published 2013“…The algorithm also utilizes certain statistical features from the EEG signal that are used as features to the classifier logic. …”
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Power quality problem classification based on Wavelet Transform and a Rule-Based method
Published 2010“…The model is tested by using MATLAB toolbox. The simulation produces satisfactory result in identifying the disturbance and proof that it is possible to use this model for power disturbance classification. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…In addition, the hyperparameter tuning problem is considered in this research to improve the developed hybrid model by using the AOA algorithm. Lastly, a new hybrid technique suggests tackling the current image encryption application problem by using the estimated parameters of chaotic systems with an optimization algorithm, the SKF algorithm. …”
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Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar
Published 2015“…The objectives of this project are to use FCM as the clustering algorithm to establish TLPs. …”
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Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method
Published 2010“…The model is tested by using MATLAB toolbox. The simulation produces satisfactory result in identifying the disturbance and proof that it is possible to use this model for power disturbance classification. …”
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Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method
Published 2010“…The model is tested by using MATLAB toolbox. The simulation produces satisfactory result in identifying the disturbance and proof that it is possible to use this model for power disturbance classification. …”
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Nature-Inspired Drone Swarming for Wildfires Suppression Considering Distributed Fire Spots and Energy Consumption
Published 2024“…Our quantitative tests show that the improved model has the best coverage (95.3%, 84.3% and 65.8%, respectively) compared to two other methods Levy Flight (LF) algorithm and Particle Swarm Optimization (PSO), which use the same initial parameter values. …”
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