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Optimal load dispatch of community microgrid with deep learning based solar power and load forecasting
A deep recurrent neural network with long short-term memory units (DRNN-LSTM) model is
developed to forecast aggregated power load and the photovoltaic (PV) power output in …
developed to forecast aggregated power load and the photovoltaic (PV) power output in …
Mixed oxide nanotubes in nanomedicine: A dead-end or a bridge to the future?
Nanomedicine has seen a significant rise in the development of new research tools and
clinically functional devices. In this regard, significant advances and new commercial …
clinically functional devices. In this regard, significant advances and new commercial …
Location-routing problem in multimodal transportation network with time windows and fuzzy demands: Presenting a two-part genetic algorithm
Distribution of products throughout a supply chain could be managed via multimodal
transportation networks. This will be more likely in long-haul transportation where a decision …
transportation networks. This will be more likely in long-haul transportation where a decision …
On the environmental performance analysis: a combined fuzzy data envelopment analysis and artificial intelligence algorithms
Greenhouse gases (GHG) remain in the atmosphere for a very long-time causing alarmingly
fast warming worldwide (global warming); especially Carbon dioxide (CO 2) emissions have …
fast warming worldwide (global warming); especially Carbon dioxide (CO 2) emissions have …
Season specific approach for short-term load forecasting based on hybrid FA-SVM and similarity concept
This paper proposes a new hybrid season specific approach to incorporate the seasonality
effect in short term load forecasting (STLF). A new season specific similarity concept (SSSC) …
effect in short term load forecasting (STLF). A new season specific similarity concept (SSSC) …
Rain-fall optimization algorithm: A population based algorithm for solving constrained optimization problems
This paper proposes rain-fall optimization algorithm (RFO), a new nature-inspired algorithm
based on behavior of raindrops, for solving of real-valued numerical optimization problems …
based on behavior of raindrops, for solving of real-valued numerical optimization problems …
Deriving operating rules for a large-scale hydro-photovoltaic power system using implicit stochastic optimization
Complementary operation is a new effective way to simultaneously manage hydropower
and photovoltaic (PV) power. With the integration of a PV power into an existing hydropower …
and photovoltaic (PV) power. With the integration of a PV power into an existing hydropower …
Long-term electrical energy consumption formulating and forecasting via optimized gene expression programming
This study formulates the effects of two different historical data types on electrical energy
consumption of ASEAN-5 counties. On this basis, optimized GEP (gene expression …
consumption of ASEAN-5 counties. On this basis, optimized GEP (gene expression …
A new approach to oil spill detection that combines deep learning with unmanned aerial vehicles
This study presents a novel approach to automatic oil spill detection, using unmanned aerial
vehicle (UAV) images to realize intelligent control in oil production. Despite considerable …
vehicle (UAV) images to realize intelligent control in oil production. Despite considerable …
Game-theoretic planning for integrated energy system with independent participants considering ancillary services of power-to-gas stations
The emergence of power-to-gas stations (P2GSes) has provided opportunities to make an
efficient use of surplus power generated from intermittent renewable energy, thus linking the …
efficient use of surplus power generated from intermittent renewable energy, thus linking the …