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

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  1. 1
    Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam

    Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

    Published 2017
    “…Next, four recently introduced optimization algorithms are employed as feature selector, namely as 1) angle modulated simulated Kalman filter (AMSKF), 2) binary simulated Kalman filter (BSKF), 3) local optimum distance evaluated simulated Kalman filter (LocalDESKF), and 4) global optimum distance evaluated simulated Kalman filter (GlobalDESKF). …”
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  2. 2
    Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach

    Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem

    Published 2019
    “…In addition, to prove the superiority of the proposed hybrid forecasting method the simulation results obtained using ANN and ANFIS models optimized by other well-known optimization methods have been compared with that of proposed method. © 2019 IEEE.…”
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  3. 3
    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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  4. 4
    Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks

    Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Ramarao, Taj, Mohammed Baloch

    Published 2008
    “…The algorithms are developed using MATLABTM software. A range of faults are simulated on EHV modeled transmission line using SimPowerSytemsTM, and the spectra of the fault data are analyzed using fast Fourier transform which facilitates extraction of distinct features of each type of fault. …”
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  5. 5
    Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks

    Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Rama Rao

    Published 2009
    “…The algorithms are developed using MATLAB software. A range of faults are simulated on EHV modeled transmission line using SimPowerSytems, and the spectra of the fault data are analyzed using fast Fourier transform to extract features of each type of fault. …”
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  6. 6
    Voting algorithms for large scale fault-tolerant systems

    Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

    Published 2011
    “…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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  7. 7
    Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines

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

    Published 2008
    “…The algorithms are developed using MATLABTM software. A range of faults are simulated using SimPowerSytemsTM and the spectra of the fault data are analyzed using Fast Fourier Transform which facilitates extraction of distinct features of each fault type. …”
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  8. 8
    Optimal selection of long time acoustic features using GA for the assessment of vocal fold disorders

    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.

    Published 2013
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  9. 9
    Autoreclosure in extra high voltage lines using taguchi's method and optimized neural networks

    Autoreclosure in extra high voltage lines using taguchi's method and optimized neural networks by K.S.R, Rao, F. D., Zahlay

    Published 2008
    “…The algorithms are developed using MATLABâ„¢ software. A range of faults are simulated on EHV modeled transmission line using SimPowerSytemsâ„¢, and the spectra of the fault data are analyzed using fast Fourier transform which facilitates extraction of distinct features of each type of fault. …”
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  10. 10
    Optimization of neural network using cuckoo search for the classification of diabetes

    Optimization of neural network using cuckoo search for the classification of diabetes by Abubakar, Adamu, Shuib, Liyana, Chiroma, Haruna

    Published 2015
    “…The high dimension of the features in our dataset triggered the study to extract the critical features using principal component analysis. …”
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  11. 11
    Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system

    Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2018
    “…SKF is compared with conventional algorithms for image template matching which are performance index value (PIM) and correlation by using DC components of image (TMC) and by using power of images (TMP) methods. …”
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  12. 12
    Performance analysis of PSO MPPT for photovoltaic (PV) system during irradiance changes / Kharismi Burhanudin

    Performance analysis of PSO MPPT for photovoltaic (PV) system during irradiance changes / Kharismi Burhanudin by Burhanudin, Kharismi

    Published 2018
    “…The process continues repeatedly to track maximum power depending on the swarmsize of the MPPT algorithm. In order to validate this technique simulation was conducted using MATLAB SIMULINK software in order to observe and identify the output power extracted from the PV panel. …”
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  13. 13
    Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun

    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

    Published 2021
    “…However, due to some drawbacks, an advanced technique was employed in this study. The proposed method involves using a convolutional neural network (CNN) with a feature extraction ability to learn from the hydrological dataset efficiently. …”
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  14. 14
    Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA

    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.

    Published 2017
    “…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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  15. 15
    ECG noise reduction technique using antlion (ALO) algorithm for heart rate monitoring devices

    ECG noise reduction technique using antlion (ALO) algorithm for heart rate monitoring devices by Hii, Kiew Hui

    Published 2020
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  16. 16
    The classification of wink-based eeg signals by means of transfer learning models

    The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

    Published 2021
    “…This study aimed to explore the performance of different pre-processing methods, namely Fast Fourier Transform, Short-Time Fourier Transform, Discrete Wavelet Transform, and Continuous Wavelet Transform (CWT) that could allow TL models to extract features from the images generated and classify through selected classical ML algorithms . …”
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  17. 17
    JOINT TORQUEESTIMATION OF sEMG SIGNALS BASED ON INTELLIGENT TECHNIQUES FOR ROBOTIC ASSISTIVE SYSTEM

    JOINT TORQUEESTIMATION OF sEMG SIGNALS BASED ON INTELLIGENT TECHNIQUES FOR ROBOTIC ASSISTIVE SYSTEM by KU ABD RAHIM, KU NURHANIM

    Published 2014
    “…Thereafter, the actual joint torque was acquired through dynamic modeling. Finally, simulation was conducted on nine mathematical models to convert the sEMG signals to estimated joint torque using optimization techniques such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO).…”
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  18. 18
    Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid

    Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid by Gaeid, Khalaf Salloum

    Published 2012
    “…There are two steps in the fault tolerant control process; in the first step the fault is identified with the feature extraction module, a fault decision module and a feature cluster module. …”
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  19. 19
    Enhancing land cover classification in remote sensing imagery using an optimal deep learning model

    Enhancing land cover classification in remote sensing imagery using an optimal deep learning model by Motwake, Abdelwahed, Hassan Abdalla Hashim, Aisha, Obayya, Marwa, Eltahir, Majdy M.

    Published 2023
    “…hyperparameter selection is accomplished with the help of the Reptile Search Algorithm (RSA). The simulation analysis was conducted upon the ISCSODL-LCC model using two benchmark datasets and the results established the superior performance of the proposed model. …”
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  20. 20
    High impedance fault detection and localization in 11kV distribution system / Mohd Syukri Ali

    High impedance fault detection and localization in 11kV distribution system / Mohd Syukri Ali by Mohd Syukri , Ali

    Published 2018
    “…Subsequent algorithm simulation results show that the proposed methods are able to detect and subsequently locate the faults with high accuracies. …”
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