Search Results - (( parameter adaptation method algorithm ) OR ( using simulation based algorithm ))
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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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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…This study proposed an improved parameter estimation procedure for PEMFCs by using the GOOSE algorithm, which was inspired by the adaptive behaviours found in geese during their relaxing and foraging times. …”
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BBO algorithm-based tuning of PID controller for speed control of synchronous machine
Published 2023Article -
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Simulated real-time controller for tuning algorithm using modified hill climbing approach
Published 2014“…Often, it is necessary to calibrate a certain parameters of a control system due to plant parameters fluctuation over time.In this research, an intelligent algorithmic tuning technique suitable for realtime system tuning based on hill climbing optimization algorithm and model reference adaptive control system (MRAC) technique is proposed. …”
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5
Using adaptive safe experimentation dynamics algorithm for maximizing wind farm power
Published 2022“…This research presents a model-free strategy for increasing wind farm power generation based on the Adaptive Safe Experimentation Dynamics Algorithm (ASEDA). …”
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6
Efficiency improvement of a standalone photovoltaic system using fuzzy-based maximum power point tracking algorithm
Published 2016“…MPPT algorithms can be categorized into classical methods and artificial intelligence-based methods. …”
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7
Effects of user selected conditions on modeling of dynamic systems using adaptive fuzzy model
Published 2001“…In this paper, major properties of an adaptive fuzzy model as a system identifier when trained by the back-propagation algorithm are discussed. …”
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8
Using adaptive safe experimentation dynamics algorithm for maximizing wind farm power production
Published 2022“…This research presents a model-free strategy for increasing wind farm power generation based on the Adaptive Safe Experimentation Dynamics Algorithm (ASEDA). …”
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9
Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Second, propose an Optimized Time Sliding Window based Three Colour Marker. Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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10
Adaptive Traffic Prioritization Algorithm Over Ad Hoc Network Using IEEE 802.11e
Published 2016“…This thesis proposes an adaptive traffic prioritization algorithm over ad hoc network using IEEE 802.11e standard that defines a set of Quality of Service enhancements for wireless LAN applications through modifications to the Media Access Control (MAC) layer. …”
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11
Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm
Published 2020“…Data-driven tools are an optimization method to find the optimal controller parameters using the system’s input and output data. …”
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12
Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter
Published 2015“…This paper proposes three steps of improvements for identification of the nonlinear dynamic system, which exploits the concept of a state-space based time domain Volterra model. The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem
Published 2023“…Hybridization in evolutionary algorithm mechanisms such as initialization methods, local searches, specific design operators, and self-adaptive parameters enhance the algorithm’s performance. …”
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14
Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor
Published 2008“…The design and optimisation of the FLC are carried out using an adaptive fuzzy inference system network that uses the backpropagation, least square and gradient algorithms. …”
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15
Single Machine Connected Infinite Bus system tuning coordination control using biogeography-based optimization algorithm
Published 2023“…The objective function J is framed using Integral square error (ISE) and the optimal parameters can be obtained by minimizing the objective function using the proposed Biogeography Based Optimization (BBO) algorithm. …”
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Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems
Published 2015“…Moreover, the ability of initialization the hidden nodes parameters using density function and recursive algorithm will help WN-OSELM to perform useful generalization facility and modeling accuracy. …”
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17
Enhanced stability and performance of the tidal energy conversion system using adaptive optimum relation-based MPPT algorithms
Published 2025“…The A-ORB algorithm integrates the optimum relation-based (ORB) approach with Hill Climb Search (HCS), along with an adaptive gain adjustment mechanism that dynamically tunes the parameter K based on power variation (ΔP). …”
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Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks
Published 2013“…In the proposed HATSC scheme, the AHP method is uese for criteria weighting, while the TOPSIS method uses for the selection technique based on a multi-criteria decision-making algorithm is proposed. …”
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20
Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman smoother adaptive filter
Published 2015“…This paper proposes three steps of improvements for identification of the nonlinear dynamic system, which exploits the concept of a state-space based time domain Volterra model. The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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