Search Results - (( based activation function algorithm ) OR ( java adaptation optimization algorithm ))
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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A comparative study of multi-objective optimal power flow based on particle swarm, evolutionary programming, and genetic algorithm
Published 2015“…This paper compares the performance of three population-based algorithms including particle swarm optimization (PSO), evolutionary programming (EP), and genetic algorithm (GA) to solve the multi-objective optimal power flow (OPF) problem. …”
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Real time nonlinear filtered-x lms algorithm for active noise control
Published 2012“…The NLFXLMS algorithm is a stochastic gradient algorithm that incorporates the derivative of a nonlinear plant model which is represented by the scaled error function (SEF) in the controller design. …”
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Thesis -
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Nonlinear FXLMS algorithm for active noise control systems with saturation nonlinearity
Published 2012“…Simulation results show that the performance of the THF-based NLFXLMS algorithm is comparable with the SEF-based NLFXLMS.…”
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Discrimination of pathological voices using systole activated neural network
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Working Paper -
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Shunt active power filter using hybrid fuzzy-proportional and crisp-integral control algorithms for total harmonic distortion improvement
Published 2016“…First, unified ADALINEs based fundamental component extraction algorithm is proposed for dual functionality. …”
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Loudspeaker nonlinearity compensation with inverse tangent hyperbolic function-based predistorter for active noise control
Published 2014“…In active noise control (ANC), the performance of the filtered-x least mean squares (FXLMS) algorithm is degraded by the saturation of the loudspeaker in the secondary path. …”
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Developing A Control Protocol Algorithm For Stimulating The Street Light System
Published 2017“…The final prototype is developed by using the control protocol algorithm to activate the system and control all the street lights simultaneously based on the presence of objects. …”
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Monograph -
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An Improved Wavelet Neural Network For Classification And Function Approximation
Published 2011“…First, the types of activation functions used in the hidden layer of the WNN were varied. …”
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VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.
Published 2012“…The efficiency of the proposed approach is evaluated by two benchmark functions. The analysis and comparison of VIGA-20 is based on convergence test against the results obtained from the Simple Genetic Algorithm. …”
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Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations
Published 2022“…The RBFNN model with softmax as the hidden layer activation function and identity as the outer layer activation function has the least predictive performance, as indicated by an R2 of 0.403 and a RMSE of 301.55. …”
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Effort Estimation Model for Function Point Measurement
Published 2007“…This research work has generated an algorithmic effort estimation model for function points measurement. …”
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Jogging activity recognition using k-NN algorithm
Published 2022“…The objective of this project are 1) to investigate human activity recognition (HAR) for jogging activity and k-Nearest Neighbors (k-NN) algorithm for jogging classifier, 2) to apply HAR AND k-NN for jogging recognition and classification and, 3) to test the functionality of the k-NN algorithm of jogging recognition and classification. …”
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Academic Exercise -
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A harmony search-based learning algorithm for epileptic seizure prediction
Published 2016“…The proposed harmony search-based learning algorithm is used in the task of epileptic seizure prediction. …”
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A robust modified model predictive control (MMPC) based on Lyapunov function for three-phase active-front-end (AFE) rectifier
Published 2023Conference Paper -
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Real time De-mixing system based on LMS adaptive algorithm for blind two source signals separation
Published 2007“…Making the real-time mixture of source signals as simultaneously as de-mixture in simulation based on adaptive NLMS and activation function in neural network are proposed. …”
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