OSUVA - Selaus tekijän "Nahavandi, Saeid" mukaan

    • A Novel Evolutionary-Based Deep Convolutional Neural Network Model for Intelligent Load Forecasting 

      Jalali, Seyed Mohammad Jafar; Ahmadian, Sajad; Khosravi, Abbas; Shafie-khah, Miadreza; Nahavandi, Saeid; Catalão, João P. S. (IEEE, 12.03.2021)
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      The problem of electricity load forecasting has emerged as an essential topic for power systems and electricity markets seeking to minimize costs. However, this topic has a high level of complexity. Over the past few years, ...
    • An advanced short-term wind power forecasting framework based on the optimized deep neural network models 

      Jalali, Seyed Mohammad Jafar; Ahmadian, Sajad; Khodayar, Mahdi; Khosravi, Abbas; Shafie-khah, Miadreza; Nahavandi, Saeid; Catalão, João P.S. (Elsevier, 10 / 2022)
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      With the continued growth of wind power penetration into conventional power grid systems, wind power forecasting plays an increasingly competitive role in organizing and deploying electrical and energy systems. The wind ...
    • An Optimized Uncertainty-Aware Training Framework for Neural Networks 

      Tabarisaadi, Pegah; Khosravi, Abbas; Nahavandi, Saeid; Shafie-Khah, Miadreza; Catalão, João P. S. (IEEE, 25.10.2022)
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      Uncertainty quantification (UQ) for predictions generated by neural networks (NNs) is of vital importance in safety-critical applications. An ideal model is supposed to generate low uncertainty for correct predictions and ...
    • Solar irradiance forecasting using a novel hybrid deep ensemble reinforcement learning algorithm 

      Jalali, Seyed Mohammad Jafar; Ahmadian, Sajad; Nakisa, Bahareh; Khodayar, Mahdi; Khosravi, Abbas; Nahavandi, Saeid; Islam, Syed Mohammed Shamsul; Shafie-khah, Miadreza; Catalão, João P.S. (Elsevier, 01.12.2022)
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      Solar irradiance forecasting is a major priority for the power transmission systems in order to generate and incorporate the performance of massive photovoltaic plants efficiently. As such, prior forecasting techniques ...
    • Towards novel deep neuroevolution models: chaotic levy grasshopper optimization for short-term wind speed forecasting 

      Jalali, Seyed Mohammad Jafar; Ahmadian, Sajad; Khodayar, Mahdi; Khosravi, Abbas; Ghasemi, Vahid; Shafie-khah, Miadreza; Nahavandi, Saeid; Catalão, João P.S. (Springer, 01.08.2022)
      article
      High accurate wind speed forecasting plays an important role in ensuring the sustainability of wind power utilization. Although deep neural networks (DNNs) have been recently applied to wind time-series datasets, their ...