A comparative analysis of the arima and lstm predictive models and their effectiveness for predicting wind speed
M Elsaraiti, A Merabet - Energies, 2021 - mdpi.com
Forecasting wind speed has become one of the most attractive topics to researchers in the
field of renewable energy due to its use in generating clean energy, and the capacity for …
field of renewable energy due to its use in generating clean energy, and the capacity for …
[HTML][HTML] A new generalization of Lindley distribution for modeling of wind speed data
M Ahsan-ul-Haq, SM Choudhary, AH AL-Marshadi… - Energy Reports, 2022 - Elsevier
The most suitable source of energy for human use is wind energy, which is competitive and
supports the energy demand of a large population. In this study, we introduced a new …
supports the energy demand of a large population. In this study, we introduced a new …
[PDF][PDF] İstatistiksel metotlar ve yapay sinir ağları kullanarak kısa dönem çok adımlı rüzgâr hızı tahmini
İ Kırbaş - Sakarya University Journal of Science, 2018 - researchgate.net
Bu çalışmada TÜBİTAK T60 ulusal gözlem evi meteoroloji istasyonunun 2016 yılı nisan ayı
içerisinde yaptığı gözlem sonuçları PHP programlama dili kullanılarak web sitesi üzerinden …
içerisinde yaptığı gözlem sonuçları PHP programlama dili kullanılarak web sitesi üzerinden …
Multi-step forward forecasting of electrical power generation in lignite-fired thermal power plant
This paper presents multi-step forward forecasting studies using real-time generated
electrical power time series. Nonlinear Automatic Regression (NAR) and Autoregressive …
electrical power time series. Nonlinear Automatic Regression (NAR) and Autoregressive …
PortWeather: A lightweight onboard solution for real-time weather prediction
Maritime journeys significantly depend on weather conditions, and so meteorology has
always had a key role in maritime businesses. Nowadays, the new era of innovative …
always had a key role in maritime businesses. Nowadays, the new era of innovative …
Short-term multi-step wind speed prediction using statistical methods and artificial neural networks
İ Kırbaş - Sakarya University Journal of Science, 2018 - dergipark.org.tr
Bu çalışmada TÜBİTAK T60 ulusal gözlem evi meteoroloji istasyonunun 2016 yılı nisan ayı
içerisinde yaptığı gözlem sonuçları PHP programlama dili kullanılarak web sitesi üzerinden …
içerisinde yaptığı gözlem sonuçları PHP programlama dili kullanılarak web sitesi üzerinden …
[PDF][PDF] A Comparative Analysis of the ARIMA and LSTM Predictive Models and Their Effectiveness for Predicting Wind Speed. Energies 2021, 14, 6782
M Elsaraiti, A Merabet - 2021 - pdfs.semanticscholar.org
Forecasting wind speed has become one of the most attractive topics to researchers in the
field of renewable energy due to its use in generating clean energy, and the capacity for …
field of renewable energy due to its use in generating clean energy, and the capacity for …
[PDF][PDF] Investigation of predictive performance of LSTM artificial neural networks on Brownian time series
I Kirbas - 2019 - researchgate.net
The data sets that the data changes over time are called time series. Time series analysis is
used in a wide area ranging from biomedical, agricultural, energy systems to forecasting and …
used in a wide area ranging from biomedical, agricultural, energy systems to forecasting and …
[PDF][PDF] Energy Reports
M Ahsan-ul-Haq, SM Choudhary, AH AL-Marshadi… - 2021 - researchgate.net
abstract The most suitable source of energy for human use is wind energy, which is
competitive and supports the energy demand of a large population. In this study, we …
competitive and supports the energy demand of a large population. In this study, we …
[PDF][PDF] Determination of Appropriate Distribution Functions for the Wind Speed Data Using the R
I Kirbas - academia.edu
Accurate determination of the proper distribution and parameters of this distribution
according to the wind characteristics of the zone is vital for wind energy investment. In …
according to the wind characteristics of the zone is vital for wind energy investment. In …