Search Results - (( parameters evaluation means algorithm ) OR ( using optimization methods algorithm ))

Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

“…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems by Zulkifli, Munierah, Abd Rahmin, Nor Aliza, Wah, June Leong

“…Stochastic gradient descent (SGD) is one of the most common algorithms used in solving large unconstrained optimization problems. …”
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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.

“…Realcoded genetic algorithm (RCGA) as a stochastic global search method was applied for optimization. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

“…Two methods of optimization are used for CBLL. They are Cross Entropy and also Genetic Algorithm. …”
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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.

“…Real-coded genetic algorithm (RCGA) as a stochastic global search method was applied for optimization. …”

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. …”

Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L., Kwong C.F.

“…To address these problems, a novel method combining a covering rough set and a K-Means clustering algorithm (RK-Means) was proposed in this paper. …”

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

“…Motivated by the limitations of the current methods, there is an advantage to using safe experimentation dynamics (SED) as a tool for optimization. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

“…Motivated by the limitations of the current methods, there is an advantage to using safe experimentation dynamics (SED) as a tool for optimization. …”
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Novel chewing cycle approach for peak detection algorithm of chew count estimation by Selamat, Nur Asmiza, Md Ali, Sawal Hamid, Ismail, Ahmad Ghadafi, Ahmad, Siti Anom, Minhad, Khairun Nisa'

“…This work proposes a novel approach to chew count estimation using particle swarm optimization (PSO) combined with a peak detection algorithm. …”
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Novel chewing cycle approach for peak detection algorithm of chew count estimation by Selamat, Nur Asmiza, Md Ali, Sawal Hamid, Ismail, Ahmad Ghadafi, Ahmad, Siti Anom, Minhad, Khairun Nisa’

“…This work proposes a novel approach to chew count estimation using particle swarm optimization (PSO) combined with a peak detection algorithm. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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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.

“…Besides, it is then used to optimize the PI parameters in order to get the desired output voltage of the PV electrical inverter along with the PWM method. …”

An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum by Darzi S., Tiong S.K., Tariqul Islam M., Rezai Soleymanpour H., Kibria S.

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

“…Besides, it is then used to optimize the PI parameters in order to get the desired output voltage of the PV electrical inverter along with the PWM method. …”
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Improving earth surface temperature forecasting through the optimization of deep learning hyper-parameters using barnacles mating optimizer by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Muhammad 'Arif, Mohamad

“…This study proposes a hybrid forecasting model for Earth surface temperature using Deep Learning (DL). To improve the DL model's performance, an optimization algorithm called Barnacles Mating Optimizer (BMO) is integrated to optimize both weights and biases. …”
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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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