Search Results - (( simulation optimization using algorithm ) OR ( parameter extraction method algorithm ))*

Characterization of PV panel and global optimization of its model parameters using genetic algorithm by Ismail M.S., Moghavvemi M., Mahlia T.M.I.

“…The Matlab-Simulink environment is used to simulate the operation of the PV module, depending on the extracted parameters. …”

Characterization of PV panel and global optimization of its model parameters using genetic algorithm by Ismail, M.S., Moghavvemi, Mahmoud, Mahlia, T.M.I.

“…The Matlab-Simulink environment is used to simulate the operation of the PV module, depending on the extracted parameters. …”
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Extraction of photovoltaic module model's parameters using an improved hybrid differential evolution/electromagnetism-like algorithm by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines by K.S.R., Rao, Z.F., Desta

“…The fault identification prior to reclosing is based on optimized artificial neural network associated with Levenberg Marquardt algorithm to train the ANN and Taguchi's Method to find optimal parameters of the algorithm and number of hidden neurons. …”
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Parameter extraction of solar photovoltaic modules using penalty-based differential evolution by Ishaque, K., Salam, Z., Mekhilef, Saad, Shamsudin, A.

“…The two diode model of a solar cell is used as the basis for the extraction problem. The analyses carried out using synthetic current-voltage (I-V) data set showed that the proposed P-DE outperforms other Evolutionary Algorithm methods, namely the simulated annealing (SA), genetic algorithm (GA), and particle swarm optimization (PSO). …”
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Optimal selection of long time acoustic features using GA for the assessment of vocal fold disorders by Sindhu, Ravindran, Neoh, Siew Chin, Dr., Muthusamy, Hariharan, Dr.

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Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA by Javed, E., Faye, I., Malik, A.S., Abdullah, J.M.

“…From the simulated data, the similarity index between the extracted BCG and the simulated BCG showed the effectiveness of the proposed method in BCG removal. …”
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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun by Chong , Kai Lun

“…In addition, the confidence level was built using the percentile-t-method (or bootstrap-t-method). …”
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ECG noise reduction technique using antlion (ALO) algorithm for heart rate monitoring devices by Hii, Kiew Hui

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Predictive Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell System by Jye Yun, Fam, Shen Yuong, Wong, Hazrul, Mohamed Basri, Mohammad Omar, Abdullah, Kasumawati, Lias, Saad, Mekhilef

“…All simulations were performed using MATLAB software to show the power characteristics extracted from the PEMFC system. …”
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Design of combined robust controller for a pneumatic servo actuator system with uncertainty by Mohd Noor, Samsul Bahari, Ali, Hazem Ibrahim, Marhaban, Mohammad Hamiruce

“…This method is used to find the optimal values of weighting functions parameters that lead to obtain an optimal H-inf-controller by minimizing the infinity norm of the transfer function of the nominal closed loop system. …”
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Adaptive Step Size Based Hill-Climb Search Algorithm for MPPT Control of DFIG-WECS With Reduced Power Fluctuation and Improved Tracking Performance by Uddin M.N., Amin I.K.

PSO modelling and PID controlled of automatic fish feeder system by W Mahmud, Wan Muhammad Azlan

“…The main objective of this study is to improve the performance of fish feeding system by using PID controller through ARX modelling. In this study, raw data at distribution part with speed of 130 rpm, 160 rpm, 190 rpm, 220 rpm and 250 rpm were extracted and used to determine ARX equation parameters as transfer function by using PSO algorithm to optimize ARX model parameter. …”
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Obso based fractional pid for mppt-pitch control of wind turbine systems by Mehedi, I.M., Al-Saggaf, U.M., Vellingiri, M.T., Milyani, A.H., Saad, N.B., Yahaya, N.Z.B.

“…The OBSO algorithm is derived from the integration of oppositional based learning (OBL) concept with the traditional BSO algorithm in order to improve the convergence rate, which is then applied to effectively choose the parameters involved in the FOPID controller. …”
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Hybrid particle swarm optimization for robust digital image watermarking by Tao, Hai, Jasni, Mohamad Zain, Abdalla, Ahmed N., Mohammad Masroor, Ahmed

“…Moreover, the work takes accomplishing maximum robustness and transparency into consideration. HPSO method is used to estimate the multiple parameters involved in the model. …”
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A new teaching learning artificial bee colony based maximum power point tracking approach for assessing various parameters of photovoltaic system under different atmospheric condit... by Dokala Janandra, Krishna Kishore

“…Besides, the performance of the Renewable Energy (RE)-based system has to be enriched with regard to settling time, accuracy, speed, and efficiency. Hence, to optimize the cost of integrating RES‘s through newly developed maximum power point tracking (MPPT) based optimization method such as grasshopper optimization algorithm (GOA) has been introduced. …”
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Predictive Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell System by Jye Yun, Fam

“…All simulations were conducted using MATLAB software to demonstrate the PEMFC power characteristics and output power extraction. …”
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Modelling of Liquid-liquid Equilibrium Behaviour of Aqueous Two-Phase Polymer Mixture System for Protein Extraction by Ahmad, Murni M

“…We solve the minimization problem using the modified Shor's R-algorithm for non-smooth optimization [3,4]. …”
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AQUEOUS TWO-PHASE POLYMER MIXTURE SYSTEM AS PROTEIN XTRACTION TECHNIQUE. MODELLING OF PROTEIN PARTITIONING BEHAVIOR by Ahmad, Murni M

“…The minimization problem is solved using the modified Shor's R-algorithm for non-smooth optimization. …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

“…Furthermore, to evaluate the efficiency of the proposed modified differential evolution for the training of ridgelet probabilistic neural network, four statistical search techniques, namely, particle swarm optimization, genetic algorithm, simulated angling, and classical differential evolution are used and their results are compared. …”
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