Search Results - (( parameter adaptation method algorithm ) OR ( parameters deviations methods algorithm ))

On the problem formulation for parameter extraction of the photovoltaic model: novel integration of hybrid evolutionary algorithm and Levenberg Marquardt based on adaptive damping... by Mohammed Ridha, Hussein, Hizam, Hashim, Mirjalili, Seyedali, Othman, Mohammad Lutfi, Ya'acob, Mohammad Effendy, Ahmadipour, Masoud, Ismaeel, Nooruldeen Q.

“…This paper presents an approach to determine the nine parameters of the three diode (TD) PV model based on the integration of the guaranteed convergence arithmetic optimization algorithm and Levenberg-Marquardt with adaptive damping nonlinear parameter method named as GCAOAAdLM. …”
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Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm by Mohd Riduwan, Ghazali

“…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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Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor by Hafz Nour, Mutasim Ibrahim

“…Both experimental and simulation results obtained from the HMRASC and the position angle estimation algorithms showed superior results compared to other methods presented in the literature.…”
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Comparison of mabsa, PSO and GWO of PI-PD controller for dc motor by Nur Naajihah, Ab Rahman

“…The swarm intelligence group selected Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Modified Adaptive Bats Sonar Algorithms (MABSA) to optimize the parameters of the PI-PD controller. …”
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Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy by Ehteram M., Ahmed A.N., Fai C.M., Afan H.A., El-Shafie A.

Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification by Petwan, Montha

“…Therefore, an improved feature extraction and selection for sky image classification (FESSIC) algorithm is proposed. This algorithm consists of (i) Gaussian smoothness standard deviation method that formulates informative features within sky images; (ii) nearest-threshold based technique that converts feature map into a weighted directed graph to represent relationship between features; and (iii) an ant colony system with self-adaptive parameter technique for local pheromone update. …”
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Artificial Bee Colony-based satellite image contrast and brightness enhancement technique using DWT-SVD by Bhandari, A.K., Soni, V., Kumar, A., Singh, G.K.

“…The method employs the ABC technique to learn the parameters of the adaptive thresholding function required for optimum enhancement. …”
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Power system stabilizer optimization using BBO algorithm for a better damping of rotor oscillations owing to small disturbances by Kasilingam G., Pasupuleti J., Bharatiraja C., Adedayo Y.

“…The simulation results indicate that when compared to other available methods, the BBO algorithm damps out low-frequency oscillations in the synchronous machine rotor in an effective manner. …”

Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller by Zaridah, Mat Zain

“…The response of the Pico-satellite is compared with a model reference adaptive system, derived on the basis of deviation in the responses and updates the adaptive gain. …”
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A comparative study of the Z-N, adaptation law and PSO methods of tuning the PID controller of a synchronous machine by Kasilingam G., Pasupuleti J.

“…A proportional–integral–derivative (PID)-based power system stabilizer (PSS) was designed to damp low-frequency oscillations in power systems under different operating conditions. The parameters of the PID controller were tuned using a particle swarm optimization (PSO) algorithm. …”

Simultaneous Adaptation Of Multiple Genetic Algorithm Parameters Using Fuzzy Logic Controllers by Ghallab, Abdullatif Saleh Nasser

“…This study aims at designing an online adaptive method to control multiple parameters of the Genetic Algorithm. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

“…The second taxonomy is a new taxonomy proposed to classify the adaptive DE algorithms in particular into two categories (DE with adaptive parameters and DE with adaptive parameters and strategies) considering the adaptive components used in this algorithm. …”
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Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm by Ehteram M., Othman F.B., Yaseen Z.M., Afan H.A., Allawi M.F., Malek M.B.A., Ahmed A.N., Shahid S., Singh V.P., El-Shafie A.

“…Decision making; Disaster prevention; Floods; Routing algorithms; Water resources; Absolute deviations; Bat algorithms; Comparative analysis; Computational time; Flood routing; Muskingum models; Particle swarm optimization algorithm; Swarm algorithms; Particle swarm optimization (PSO); accuracy assessment; algorithm; comparative study; decision making; flood; flood forecasting; flood routing; numerical method; optimization; parameter estimation; water resource; United Kingdom; United States…”

Novel parameter extraction for single, double, and three diodes photovoltaic models based on robust adaptive arithmetic optimization algorithm and adaptive damping method of Berndt-Hall-Hall-Hausman by Mohammed Ridha, Hussein, Hizam, Hashim, Mirjalili, Seyedali, Othman, Mohammad Lutfi, Ya'acob, Mohammad Effendy, Ahmadipour, Masoud

“…In this work, we present a robust adaptive Arithmetic Optimization Algorithm based on the adaptive damping Berndt-hall-hall-Hausman (RaAOAAdBHHH) approach to efficacity determine the parameters of the single, double, and three diode PV model. …”
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A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

Novel Robot Manipulator Adaptive Artificial Control: Design a Novel SISO Adaptive Fuzzy Sliding Algorithm Inverse Dynamic Like Method. by Sulaiman, Nasri, Piltan, Farzin, Nasiri, Hajar, Allahdadi, Sadeq, Bairami, Mohamad Amin

“…In order to solve this problem this research is focoused on two methodology the first one is design a fuzzy inference system as a estimate nonlinear part of main controller but this method caused to high computation load in fuzzy rule base and the second method is focused on design novel adaptive method to reduce the computation in fuzzy algorithm.…”
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Classification of transient disturbance using Wavelet based support vector machine / Fahteem Hamamy Anuwar by Anuwar, Fahteem Hamamy

“…In this research, Multilayer perception (MLP) of feedforward Artificial Neural Network (ANN) has also been used as the classifier and comparison are made between the SVM and ANN method. The SVM results show that RBF kernel is superior to linear kernel in classifying the transient with average percentage of 83% This research has also proved that SVM has higher performance than the backpropagation algorithm of the ANN.…”
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A hybrid metaheuristic algorithm for identification of continuous-time Hammerstein systems by Jui, Julakha Jahan, Mohd Ashraf, Ahmad

“…The results showed that the proposed method was efficient in identifying both the Hammerstein model subsystems in terms of the quadratic output estimation error and parameter deviation index. …”
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Heterogenous adaptive ant colony optimization with 3-opt local search for the travelling salesman problem by Tuani Ibrahim, Ahamed Fayeez, Keedwell, Edward, Collett, Matthew

“…One method to mitigate this is to introduce adaptivity into the algorithm to discover good parameter settings during the search. …”
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The effect of adaptive parameters on the performance of back propagation by Abdul Hamid, Norhamreeza

“…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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