Search Results - (( parameter extraction method algorithm ) OR ( variable selection problem algorithm ))

CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

“…To overcome these ANN problems, the Genetic Algorithm (GA) has been most frequently used for this purpose, however, some drawbacks of GA include, slow search speed and dependence on initial parameters. …”
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Perturbation stochastic model updating of a bolted structure / Mohamad Azam Shah Aziz Shah by Aziz Shah, Mohamad Azam Shah

“…The SMU method based on the improved model was used to predict the variability of the dynamic behaviour of the structure. …”
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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…”

Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers by Uraibi, Hassan S.

“…To overcome the instability selection problem, a stability selection approach is put forward to enhance the performance of single-split variable selection method. …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Saraf, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

“…The literature contains various meta-heuristic algorithms with variable length searching. All of them enable searching in high dimensional problems. …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Saraf, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

“…The literature contains various meta-heuristic algorithms with variable length searching. All of them enable searching in high dimensional problems. …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Sara, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

“…The literature contains various meta-heuristic algorithms with variable length searching. All of them enable searching in high dimensional problems. …”
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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.

“…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”

Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…ACOMV-SVM algorithm is able to simultaneously tune SVM parameters and feature subset selection. …”
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A New Quadratic Binary Harris Hawk Optimization For Feature Selection by Abdullah, Abdul Rahim, Too, Jing Wei, Mohd Saad, Norhashimah

“…However, the original HHO is developed to solve the continuous optimization problems, but not to the problems with binary variables. …”
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Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

“…Algorithms; Diodes; Errors; Extraction; Iterative methods; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Differential evolution algorithms; Diode modeling; Electromagnetism-like algorithm; Fast convergence speed; Hybrid evolutionary algorithm; IV characteristics; Photovoltaic model; Root mean square errors; Evolutionary algorithms…”

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

“…Experimental data-oriented parameter extraction helps in giving an accurate assessment to forecast the output current of the photovoltaic cells. …”
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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

“…However, in practice, high leverage points may lead to misleading results in solving variable selection problems. Therefore, a robust sure independence screening procedure based on the weighted correlation algorithm of MRFCH for high dimensional data is developed to address this problem. …”
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Extracting crown morphology with a low-cost mobile LiDAR scanning system in the natural environment by Wang, Kai, Zhou, Jun, Zhang, Wenhai, Zhang, Baohua

“…Finally, morphological parameters of the canopy, such as crown height, crown diameter, and crown volume, are extracted using statistical and voxel methods. …”
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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.

SURE-Autometrics algorithm for model selection in multiple equations by Norhayati, Yusof

“…Its application on real data indicated that several models are able to forecast accurately if the data has no quality problem. This automatic model selection algorithm is better than non-algorithm procedure which requires knowledge and extra time. …”
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A novel theoretical and practical methodology for extracting the parameters of the single and double diode Photovoltaic models by Mohammed Ridha, Hussein, Hizam, Hashim, Mirjalili, Seyedali, Othman, Mohammad Lutfi, Ya’acob, Mohammad Effendy, Abualigah, Laith

“…However, there is no method to date that can guarantee the extracted parameter of the PV model is the most accurate one. …”
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Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

“…However, SVM suffers two main problems which include feature subset selection and parameter tuning. …”
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