Search Results - (( data evaluation method algorithm ) OR ( parameters iteration method algorithm ))

Parameter extraction of photovoltaic module using hybrid evolutionary algorithm by Muhsen D.H., Ghazali A.B., Khatib T.

“…Algorithms; Diodes; Extraction; Iterative methods; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Different evolutions; Differential Evolution; Diode modeling; Electromagnetism-like algorithm; Extracting parameter; Hybrid evolutionary algorithm; Photovoltaic model; Photovoltaic modules; Evolutionary algorithms…”

VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

“…This method is used to reduce the stochastic of data generation as the second iteration will have influence of the first iteration data. …”
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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

“…It is an iterative algorithm with descent properties that reduces computational cost by using derivatives of random data points. …”
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm by Ismail M.S., Moghavvemi M., Mahlia T.M.I.

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Model selection approaches of water quality index data by Kamarudin, Nur Azulia, Ismail, Suzilah

“…In order to select the best model, it is vital to ensure that proper estimation method is chosen in the modelling process.Different estimators have been proposed for the estimation of parameters of a model, including the least square and iterative estimators.This study aims to evaluate the forecasting performances of two algorithms on water quality index (WQI) of a river in Malaysia based on root mean square error (RMSE) and geometric root mean square error (GRMSE).Feasible generalised least squares (FGLS) and iterative maximum likelihood (ML) estimation methods are used in the algorithms, respectively.The results showed that SUREMLE-Autometrics has surpassed SURE-Autometrics; another simultaneous selection procedure of multipleequation models.Two individual selections, namely Autometrics-SUREMLE and Autometrics-SURE, though showed consistency only for GRMSE.All in all, ML estimation is a more appropriate method to be employed in this seemingly unrelated regression equations (SURE) model selection.…”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

“…Notably, the SPSA and GSPSA based methods only produced the optimal design parameter at the final iteration while it may keep a better design parameter during the tuning process if it has a memory feature. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

“…Notably, the SPSA and GSPSA based methods only produced the optimal design parameter at the final iteration while it may keep a better design parameter during the tuning process if it has a memory feature. …”
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Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method by Ramachandran, Murugan, Sundaram, Arunachalam, Ridha, Hussein Mohammed, Mirjalili, Seyedali

“…EHGSOAdBHHH exhibits outstanding accordance with attained experimental data compared with other algorithms, and its superiority is validated using several statistical criteria.…”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

“…Secondly, the modeling method of the proposed PV module is validated by experimental data. …”
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Comparison of several improved versions of particle swarm optimizer algorithm for parameter estimation of squirrel-cage induction motors / Mohammad Yazdani-Asrami, Mehran Taghipour... by Gorjikolaie, Mehran Taghipour, Gholamian, S. Asghar

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A combinatory algorithm of univariate and multivariate gene selection by Mahmoodian, Sayed Hamid, Marhaban, Mohammad Hamiruce, Abdul Rahim, Raha, Rosli, Rozita, Saripan, M. Iqbal

“…The results show that the mean of misclassification error of training samples in 100 iteration are almost equal in two algorithms but our algorithm have the better ability to classify independent samples.…”
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Power System State Estimation In Large-Scale Networks by NURSYARIZAL MOHD NOR, NURSYARIZAL

“…The gain and the Jacobian matrices associated with the basic algorithm require large storage and have to be evaluated at every iteration, resulting in more computation time. …”
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Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali, Mohd Helmi, Suid, Mohd Zaidi, Mohd Tumari

“…These results underscore the efficacy of the SEDA method in providing optimal PID control parameters while reducing computational burdens by 52% compared to other multi-agent optimization-based methods.…”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

“…For the proposed technique of the FID3-DBD algorithm, the continuous and discrete (integer) attributes would be defined in the linguistic values of the fuzzy sets, and the FUZZYDBD method is being used to set up the fuzzy sets’ parameters. …”
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Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak by Emily Sing Kiang, Siew

“…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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Efficient management of Top-k queries over Uncertain Data Streams with dynamic Sliding Window Model by Raja Wahab, Raja Azhan Syah

“…The experiments in this study compare the SWMTop-kDelta algorithm with two previous researchers and two baseline approach algorithms to evaluate their effectiveness. …”
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Effect of iterative reconstruction algorithm levels on noise index and figure-of-merit in CT pulmonary angiography examinations by Haspiharun, Hanif, Abdul Karim, Muhammad Khalis, Abbas, Zulkifly, Sabarudin, Akmal, Muniandy, S. C., Ibrahim, M. J.

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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 Manufacturer's Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. …”
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Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network by Ismail Abdullah, Kalid Abdlkader Marsal