Search Results - (( parameter adaptation modified algorithm ) OR ( evolution classification problems algorithm ))
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The effect of adaptive parameters on the performance of back propagation
Published 2012“…Thus, this research proposed a new method known as Back Propagation Gradient Descent with Adaptive Gain, Adaptive Momentum and Adaptive Learning Rate (BPGD-AGAMAL) which modifies the existing Back Propagation Gradient Descent algorithm by adaptively changing the gain, momentum coefficient and learning rate. …”
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Differential evolution for neural networks learning enhancement
Published 2008“…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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A Modified ACO-based Search Algorithm for Detecting Protein Functional Module From Protein Interaction Network
Published 2015“…Some shortcomings were identified and addressed by proposing a Modified Ant Colony Optimization Algorithm (ACO-PFMDM), which introduces two new scheme for controlling the two main parameters of ACO to solve PFMDP. …”
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A New Quadratic Binary Harris Hawk Optimization For Feature Selection
Published 2019“…In this study, twenty-two datasets collected from the UCI machine learning repository are used to validate the performance of proposed algorithms. A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
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QR Decomposition For Adaptive Filtering Application
Published 2011“…An adaptive filter is a self modifying digital filter that adjusts its parameters in order to minimize a defined error function. …”
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Using adaptive safe experimentation dynamics algorithm for maximizing wind farm power
Published 2022“…The convergence accuracy is predicted to be enhanced further by adding the adaptive element to the modified SED equation. The ASEDA-based technique is used to determine the ideal control parameter for each turbine to maximize a wind farm's total power generation. …”
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Using adaptive safe experimentation dynamics algorithm for maximizing wind farm power production
Published 2022“…The convergence accuracy is predicted to be enhanced further by adding the adaptive element to the modified SED equation. The ASEDA-based technique is used to determine the ideal control parameter for each turbine to maximize a wind farm's total power generation. …”
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Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
Published 2018“…A trend that has emerged recently is to make the algorithm parameters automatically adapt to different problems during optimization, thereby liberating the user from the tedious and time-consuming task of manual setting. …”
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Fuzzy adaptive emperor penguin optimizer for global optimization problems
Published 2023“…To alleviate this parameter tuning problem, an adaptive mechanism can be introduced in EPO. …”
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ADAPTIVE LINEAR ALGORITHMS FOR POWER SYSTEM FUNDAMENTAL AND HARMONIC ESTIMATION
Published 2015“…Hence, one of the objectives of this thesis is to address and enhance the introduced fundamental frequency adaptive filter method which was based on modified variable step size LMS (MVSS) algorithm using generalized square error normalized LMS algorithm. …”
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Feature selection optimization using hybrid relief-f with self-adaptive differential evolution
Published 2017“…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition
Published 2024“…Therefore, a modified PSO hybridized with adaptive local search (MPSO-HALS) is designed as a robust, real-time MPPT algorithm. …”
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Artificial fish swarm optimization for multilayer network learning in classification problems
Published 2012“…Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN.In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems.The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems
Published 2012“…In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems. The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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Modified Parameters of Harmony Search Algorithm for Better Searching
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…Therefore, this thesis aims to solve the feature selection problem in EMG signals classification and improve the classification performance of EMG pattern recognition system. …”
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Efficiency improvement of a standalone photovoltaic system using fuzzy-based maximum power point tracking algorithm
Published 2016“…This thesis proposes a FLC controller that calculates the E and the previous duty ratio variations (ΔDn-1) as input parameters to adaptively modify the output duty ratio (Δd). …”
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A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…The Takagi-Sugeno-Kang (TSK) type fuzzy inference system was chosen and constructed by an automatic generation of clusters as well as membership functions and minimal rules through the use of hybrid fuzzy clustering and the modified apriori algorithms respectively. The developed TSK type fuzzy inference engine is called modified adaptive fuzzy inference engine (MAFIE) and its parameters were then adjusted by the hybrid learning algorithm using adaptive neural network architecture towards improved performance which is called MANFIE. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…Differential evolution (DE) is a simple yet powerful evolutionary algorithm (EA). …”
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