2020 IEEE 8th R10 Humanitarian Technology Conference (R10-Htc) 2020
DOI: 10.1109/r10-htc49770.2020.9356988
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Solar Irradiance Prediction Based on Weather Patterns Using Bagging-Based Ensemble Learners with Principal Component Analysis

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Cited by 7 publications
(3 citation statements)
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“…The base learner in the ensemble was a pre-processed stacked LSTM model. The study showed that bagging-based ensemble learners outperformed individual learners in terms of accuracy, as evidenced by multiple metrics [195]. Another EL method used in renewable energy forecasting is the boosting technique.…”
Section: Ensemble Learning For Renewable Energy Forecastingmentioning
confidence: 93%
“…The base learner in the ensemble was a pre-processed stacked LSTM model. The study showed that bagging-based ensemble learners outperformed individual learners in terms of accuracy, as evidenced by multiple metrics [195]. Another EL method used in renewable energy forecasting is the boosting technique.…”
Section: Ensemble Learning For Renewable Energy Forecastingmentioning
confidence: 93%
“…The base learner in the ensemble was a pre-processed stacked LSTM model. The study showed that the Bagging-based ensemble learners outperformed individual learners in terms of accuracy, as evidenced by multiple metrics [187]. Another EL method used in renewable energy forecasting is the Boosting technique.…”
Section: Elm For Renewable Energy Forecastingmentioning
confidence: 95%
“…Thornthwaite potential evapotranspiration (PET Th ) is a referential measure characterized by the mathematical relationships of environmental parameters such as the average monthly possible sunshine hour (N, h/day), number of days of each month (m, days), mean temperature (T m , • C), heat index (I, unitless), and extended heat index (α, unitless) (1-3). Here, N, m, T m , I, and α were set to minimum and maximum threshold pairs of [6.2 to 11.3 h/day], [29 to 31 days/month], [25.483 to 32.483 • C], [12.8 to 15.3], and [−6.9 to −4.3] based on initial acquired experimented data of the Philippines from 2019 to 2021 [38][39][40]. The goal of this stage was to optimize the modified PET Th (PET Th-mod ) as a function of {N, T m , I, α} (4), serving as the fitness function, through minimization using atom search (ASO), differential evolution (DE), and multiverse optimization (MVO) to reduce plant stress due to drought when there is substantial high temperature (Figure 3).…”
Section: Thornthwaite Evapotranspiration Optimization Using Advanced ...mentioning
confidence: 99%