Search Results - (( parameter evaluation system algorithm ) OR ( parameter optimization means algorithm ))

A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA) by Ainul, H. M. Y., Salleh, S. M., Halib, N., Taib, H., Fathi, M. S.

“…The influence of conventional genetic algorithm parameter - generation gap has been investigated too. …”
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Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links by Arif, M., Khan, S.S., Qadri, S.S.U., Naseem, I., Moinuddin, M.

“…Moreover, for the proposed NL-qILMS, we also devised various time-varying techniques for the selection of the optimal q-parameter to improve the performance. Furthermore, the closed-form solutions for the steady-state mean square deviation, excess mean square deviation and mean square error are derived. …”
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Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA) by Ainul, H. M. Y., Salleh, S. M., Halib, N., Taib, H., Fathi, M. S.

“…The influence of conventional genetic algorithm parameter - generation gap has been investigated too. …”

ANN-Based Binary Backtracking Search Algorithm for VPP Optimal Scheduling and Cost-Effective Evaluation by Hannan M.A., Abdolrasol M.G., Mohamed R., Al-Shetwi A., Ker P., Begum R., Muttaqi K.

Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”

Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane by Julakha, Jahan Jui, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

“…The efficiency of the proposed HMVOSCA algorithm is evaluated using the convergence curve, parameter estimation error, bode plot, function plot, and Wilcoxon's test method. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

“…Hence, a memory-based optimization tool has good potential to retain the optimal design parameter during the PID tuning process. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

“…Hence, a memory-based optimization tool has good potential to retain the optimal design parameter during the PID tuning process. …”
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Optimization Of Pid Controller For Double-Link Flexible Robotic Manipulator Using Metaheuristic Algorithms by Annisa, Jamali, Intan Zaurah, Mat Darus, Hanim, Mohd Yatim, Mat Hussin, Ab Talib

“…This research focus on population-based metaheuristic that is particle swarm optimization (PSO) and artificial bees algorithm (ABC) to tune the PID control parameters of the system. …”
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An intelligent voltage controller for a PV inverter system using simulated annealing algorithm-based PI tuning approach by Najeeb M., Razali R., Daniyal H., Mahmood A., Mansor M.

“…This study associates an intelligent voltage controller based PI approach for PV electrical inverter by employing a meta-heuristic optimization algorithmic called a Simulated Annealing (SA) algorithm. …”

An Intelligent Voltage Controller for a PV Inverter System Using Simulated Annealing Algorithm-Based PI Tuning Approach by Najeeb, Mushtaq, Muhamad, Mansor, Ramdan, Razali, Hamdan, Daniyal, Ali, Mahmood

“…This study associates an intelligent voltage controller based PI approach for PV electrical inverter by employing a meta-heuristic optimization algorithmic called a Simulated Annealing (SA) algorithm. …”
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Feature optimization with metaheuristics for Artificial Neural Network-based chiller power prediction by Nor Farizan, Zakaria, Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…The algorithm identified seven optimal features primarily comprising temperature and humidity parameters. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

“…Afterward, a genetic algorithm-based optimization framework was designed to improve the interpretability and accuracy of the proposed fuzzy-tabu controller by optimizing the parameters of the FLC and also some of the planner’s parameters in order to improve the quality of the generated paths and runtimes of the planner and also to decrease the variation of the results in different runs of the planner. …”
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Identification of continuous-time hammerstein model using improved archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Cho, Bo Wen

“…This proposed algorithm produced solutions with superior accuracy and consistency compared to various established metaheuristic strategies, including particle swarm optimizer, grey wolf optimizer, multi-verse optimizer, AOA, and a hybrid optimizer (average multi-verse optimizer-sine-cosine algorithm).…”
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A static jobs scheduling for independent jobs in Grid Environment by using Fuzzy C-Mean and Genetic algorithms by Lorpunmanee, Siriluck, Md. Sap, Mohd. Noor, Abdullah, Abdul Hanan, Srinoy, Surat

“…We present a static job scheduling algorithm by using Fuzzy C-Mean and Genetic algorithms. …”
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Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation by Kumar, A., Ridha, S., Ganet, T., Vasant, P., Ilyas, S.U.

“…The impact of each input parameter affecting the pressure drop is quantified using the RF algorithm. …”
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Zero root-mean-square error for single- and double-diode photovoltaic models parameter determination by Mohammed Ridha, Hussein, Hizam, Hashim, Mirjalili, Seyedali, Othman, Mohammad Lutfi, Ya’acob, Mohammad Effendy

“…This may be extremely helpful both practically and theoretically in the PV system simulation, optimization, and evaluation. Numerous stochastic methods have been widely utilized in recent decades to tackle the parameter extraction optimization problem. …”
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Renewable sources-based automatic load frequency control of interconnected systems using chaotic atom search optimization by Irudayaraj, Andrew Xavier Raj, Abdul Wahab, Noor Izzri, Premkumar, Manoharan, Mohd Radzi, Mohd Amran, Sulaiman, Nasri, Veerasamy, Veerapandiyan, Farade, Rizwan A., Islam, Mohammad Zohrul

“…Initially, the proposed IASO is validated using a classical benchmark function and its performance is compared with ASO algorithm. Test results indicate that the proposed algorithm outperforms in terms of mean, standard deviation, and best values. …”
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PID-PSO DC motor position controller design for ankle rehabilitation system by Azizi, Muhammad Azizul Raziq

“…Hence, position control of DC motors has attracted considerable research with applied control system algorithms. This research aims to determine the mathematical modeling gain of the third-order transfer function for the DC motor that represents the features parameter of the Ankle Rehabilitation System. …”
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