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  1. 1
    Performance analyses of various photovoltaic power plant based on local spectral irradiances in Malaysia using genetic algorithm

    Performance analyses of various photovoltaic power plant based on local spectral irradiances in Malaysia using genetic algorithm by Lim, Song Wei

    Published 2023
    “…Besides, the genetic algorithm has showed that it is an effective and efficient way to perform estimation of optimal tilt angle and orientation angle for solar sites with genetic algorithm as it is able to produce correct and accurate result in a short amount of time.…”
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  2. 2
    Removal of heavy metals from water by functionalized carbon nanotubes with deep eutectic solvents: An artificial neural network approach / Seef Saadi Fiyadh

    Removal of heavy metals from water by functionalized carbon nanotubes with deep eutectic solvents: An artificial neural network approach / Seef Saadi Fiyadh by Seef Saadi , Fiyadh

    Published 2019
    “…Moreover, various indicators were implemented to evaluate the ANN model’s productivity including relative root mean square error (RRMSE), mean square error (MSE), root mean square error (RMSE), mean absolute percentage error (MAPE) and relative error (RE). …”
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  3. 3
    Implementation of a modified incremental conductance MPPT algorithm with direct control based on a fuzzy duty cycle change estimator using dSPACE

    Implementation of a modified incremental conductance MPPT algorithm with direct control based on a fuzzy duty cycle change estimator using dSPACE by Radjai, T., Rahmani, L., Mekhilef, Saad, Gaubert, J.P.

    Published 2014
    “…Maximum power point tracking (MPPT) is a necessary function in all photovoltaic (PV) systems. The classic incremental conductance (IC) MPPT algorithm is widely used in the literature. …”
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  4. 4
    Segmentation of MRI brain images using statistical approaches

    Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

    Published 2011
    “…Noise is one of the obstacles for brain MRI segmentation. The non-Local means (NL-means) algorithm is a state-of-the art neighbourhood-based noisereduction method which is time-consuming and its accuracy can be improved. …”
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  5. 5
    A robust parameter estimation approach based on stochastic fractal search optimization algorithm applied to solar PV parameters

    A robust parameter estimation approach based on stochastic fractal search optimization algorithm applied to solar PV parameters by Rezk H., Babu T.S., Al-Dhaifallah M., Ziedan H.A.

    Published 2023
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  6. 6
    Artificial Neural Network based Battery Management System on State of Charge Estimation for Optimal Operation of Photovoltaic-Battery Integrated System

    Artificial Neural Network based Battery Management System on State of Charge Estimation for Optimal Operation of Photovoltaic-Battery Integrated System by Md Ohirul Qays, Joarder Akash

    Published 2020
    “…The proposed control algorithm estimates SOC by Backpropagation Neural Network (BPNN) scheme and implements Maximum Power Point Tracking (MPPT) system of the solar panels to take decision for charging, discharging or islanding mode of the Lead-Acid battery bank. …”
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  7. 7
    Designing a control system based on SOC estimation of BMS for PV-Solar system

    Designing a control system based on SOC estimation of BMS for PV-Solar system by Buswig, Yonis.M.Yonis, Qays, Ohirul, Affam, Azuka, Hani, Albalawi, Norhuzaimin, Julai, Al-Khalid, Oth­man, Sim, Sy Yi

    Published 2020
    “…The proposed control algorithm estimates SOC by Backpropagation Neural Network (BPNN) scheme and utilizesthe Maximum Power PointTracking(MPPT)schemeof the solar panels to take decision for charging, discharging or islanding mode of the Lead-Acid battery bank. …”
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  8. 8
    Weather prediction system using ANN algorithm / Nur Afiqah Ahmad Sukri

    Weather prediction system using ANN algorithm / Nur Afiqah Ahmad Sukri by Ahmad Sukri, Nur Afiqah

    Published 2024
    “…The performance of the model is evaluated using metrics such as mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), precision, recall, F1-score, and accuracy. …”
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  9. 9
    Analysis and evaluation of various aspects of solar radiation in the Palestinian territories

    Analysis and evaluation of various aspects of solar radiation in the Palestinian territories by Ismail M.S., Moghavvemi M., Mahlia T.M.I.

    Published 2023
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  10. 10
    Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm

    Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm by Nejad, Mohsen Fadaee

    Published 2013
    “…Multi-objective optimization of HRES by Evolutionary Algorithm have become attractive in recent years due to the effectiveness of such algorithms for complicated problems. …”
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  11. 11
    Disparity Refinement Process Based On Ransac Plane Fitting For Machine Vision Applications

    Disparity Refinement Process Based On Ransac Plane Fitting For Machine Vision Applications by Hamzah, Rostam Affendi, Kadmin, Ahmad Fauzan, Abd Gani, Shamsul Fakhar, Hamid, Mohd Saad, Salam, Saifullah

    Published 2017
    “…The performance evaluations are based on standard image quality metrics i.e. structural similarity index measure, peak signal-to-noise ratio and mean square error.…”
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  12. 12
    Intelligent algorithm based modeling of renewable and green energy resources for microgrid optimization

    Intelligent algorithm based modeling of renewable and green energy resources for microgrid optimization by Khamis, Alias

    Published 2025
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  13. 13
    Evaluation of retinal vascular calibers in overweight an obese Malay children

    Evaluation of retinal vascular calibers in overweight an obese Malay children by Siang, Chai Khai

    Published 2017
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  14. 14
    Analysing the accuracy of machine learning techniques to develop an integrated influent time series model: case study of a sewage treatment plant, Malaysia

    Analysing the accuracy of machine learning techniques to develop an integrated influent time series model: case study of a sewage treatment plant, Malaysia by Ansari, Mozafar, Othman, Faridah, Abunama, Taher, El-Shafie, Ahmed

    Published 2018
    “…In this research, the influent flow rate of a sewage treatment plant (STP) was modelled and predicted by autoregressive integrated moving average (ARIMA), nonlinear autoregressive network (NAR) and support vector machine (SVM) regression time series algorithms. To evaluate the models’ accuracy, the root mean square error (RMSE) and coefficient of determination (R2) were calculated as initial assessment measures, while relative error (RE), peak flow criterion (PFC) and low flow criterion (LFC) were calculated as final evaluation measures to demonstrate the detailed accuracy of the selected models. …”
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  15. 15
    Linear and stratified sampling-based deep learning models for improving the river streamflow forecasting to mitigate flooding disaster

    Linear and stratified sampling-based deep learning models for improving the river streamflow forecasting to mitigate flooding disaster by Afan H.A., Yafouz A., Birima A.H., Ahmed A.N., Kisi O., Chaplot B., El-Shafie A.

    Published 2023
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  16. 16
    Development of soft computing prediction model for the influent physicochemical characteristics of sewage treatment plants / Mozafar Ansari

    Development of soft computing prediction model for the influent physicochemical characteristics of sewage treatment plants / Mozafar Ansari by Mozafar , Ansari

    Published 2021
    “…To find the best modelling results, the root-mean-square error (RMSE) and coefficient of determination (R2) were used as primary evaluation criteria, and relative error (RE) and Nash–Sutcliffe efficiency (NSC) were applied as secondary validation indices. …”
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  17. 17
    A cognitive mapping approach in real-time haptic rendering interaction for improved spatial learning ability among autistic people / Kesavan Krishnan

    A cognitive mapping approach in real-time haptic rendering interaction for improved spatial learning ability among autistic people / Kesavan Krishnan by Kesavan , Krishnan

    Published 2024
    “…The constructed framework was evaluated by expert reviews from the perspective of different scholars and re-designed based on the expert reviews. …”
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  18. 18
    Hardware-in-the-loop study of a hybrid active force control scheme of an upper-limb exoskeleton for passive stroke rehabilitation

    Hardware-in-the-loop study of a hybrid active force control scheme of an upper-limb exoskeleton for passive stroke rehabilitation by Anwar, P. P. Abdul Majeed

    Published 2018
    “…A hardware-in-the-loop simulation is carried out to evaluate the appropriate gains of both the PD and the AFC inertial parameter gained that is tuned via the SKF algorithm. …”
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  19. 19
    Hardware-in-the-loop study of a hybrid active force control scheme of an upper-limb exoskeleton for passive stroke rehabilitation

    Hardware-in-the-loop study of a hybrid active force control scheme of an upper-limb exoskeleton for passive stroke rehabilitation by Anwar, P. P. Abdul Majeed

    Published 2018
    “…A hardware-in-the-loop simulation is carried out to evaluate the appropriate gains of both the PD and the AFC inertial parameter gained that is tuned via the SKF algorithm. …”
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  20. 20
    Profit Optimization of a Refrigerated Gas Plant

    Profit Optimization of a Refrigerated Gas Plant by Yusoff, Nooryusmiza, Ramasamy , Marappagounder, Yusup, Suzana

    Published 2007
    “…This requires continuous re-evaluation of the operating conditions through an efficient optimization algorithm. …”
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