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  1. 1
    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589)

    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589) by Mansor, Rosnalini, Mat Kasim, Maznah, Othman, Mahmod, Zaini, Bahtiar Jamili

    “…Hence, the WeSuSFTS algorithm succeeds to improve the MH-ELD forecasting accuracy.…”
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  2. 2
    Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting

    Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting by Rosnalini, Mansor

    Published 2021
    “…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of four main phases; data pre-processing, model development, model implementation and model evaluation. …”
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  3. 3
    Weighted subsethood segmented fuzzy time series for moving holiday electricity load demand forecasting

    Weighted subsethood segmented fuzzy time series for moving holiday electricity load demand forecasting by Mansor, R., Kasim, M.M., Othman, M.

    Published 2020
    “…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of three main phases; data pre-processing, forecasting based on WeSuSFTS model and model evaluation. …”
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  4. 4
    An enhanced support vector regression -African Buffalo optimisation algorithm for electricity time series forecasting

    An enhanced support vector regression -African Buffalo optimisation algorithm for electricity time series forecasting by Maijama'a, Inusa Sani

    Published 2023
    “…Combining the enhanced algorithms results in SVR-eABO, whose forecasting ability has been assessed using MAE, MAPE, RMSE, PA and R2. …”
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  5. 5
    Optimizing wavelet neural networks using modified cuckoo search for multi-step ahead chaotic time series prediction

    Optimizing wavelet neural networks using modified cuckoo search for multi-step ahead chaotic time series prediction by Ong, Pauline, Zainuddin, Zarita

    Published 2019
    “…In this paper, a novel strategy known as the modified cuckoo search algorithm (MCSA), is proposed for WNNs initialization in order to improve its generalization performance. …”
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  6. 6
    Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications

    Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications by Sabry, Ahmad H., Wan Hasan, Wan Zuha, Ab Kadir, M. Zainal A., Mohd Radzi, Mohd Amran, Shafie, Suhaidi

    Published 2018
    “…Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. …”
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  7. 7
    Adaptive complex neuro-fuzzy inference system for non linear modeling and time series prediction

    Adaptive complex neuro-fuzzy inference system for non linear modeling and time series prediction by Shoorangiz, Mohammadreza

    Published 2013
    “…Afterward, the performance of proposed method has been evaluated using five different systems consisting of nonlinear function modelings, nonlinear dynamic modeling, chaotic dynamic prediction and sunspot dataset forecasting. …”
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  8. 8
    Investigating the reliability of machine learning algorithms as an advanced tool for ozone concentration prediction

    Investigating the reliability of machine learning algorithms as an advanced tool for ozone concentration prediction by Ayman Mohammed Shaher Yafouz, Mr.

    Published 2023
    “…The standalone and hybrid models have been tested to evaluate their performance via 5 metrics performances; (Coefficient of Determination (R2), Normalized Root Mean Square Error (NRMSE), Root Mean Square Error (RMSE), Mean Square Error (MSE), Mean Absolute Error (MAE)), and Modified Taylor Diagram. …”
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  9. 9
    Meta-cognitive Recurrent Recursive Kernel OS-ELM for concept drift handling

    Meta-cognitive Recurrent Recursive Kernel OS-ELM for concept drift handling by Liu, Zongying, Loo, Chu Kiong, Seera, Manjeevan

    Published 2019
    “…Experimental results indicate the meta-RRKOS-ELM with DDM has superior prediction ability in the different predicting horizons as compared with other algorithms.…”
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  10. 10
    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani

    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

    Published 2018
    “…In the former it is necessary to forecast the wind speed at first, then the corresponding power is obtained from the wind-power curve. …”
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