Explainable AI and optimized solar power
This paper proposes a model called X-LSTM-EO, which integrates explainable artificial intelligence (XAI), long short-term memory
Renewable Energy
You can use this model to evaluate the operational characteristics of producing green hydrogen over a 7-day period by power from a solar
Machine Learning-Driven Analysis and Prediction of Solar Power
This research explores and investigates the use of Machine Learning (ML) to study, analyse, predict and visualize solar power generation. Using real time data f
Artificial intelligence based hybrid solar energy
This research proposes a novel AI-enhanced hybrid solar energy framework integrating spatio-temporal forecasting, adaptive
Solar Power Generation in Smart Cities Using an
The construction of a drive mechanism for TP power generation in a contemporary metropolis, the modelling of a solar energy
Machine Learning Models for Solar Power
This research delves into a comparative analysis of two machine learning models, specifically the Light Gradient Boosting
Predicting Solar Energy Generation with Machine Learning based
We explore the influence of the Air Quality Index and weather features on solar energy generation, employing advanced Machine Learning and Deep Learning techniques.
SPXAI: Solar Power Generation with Explainable AI Technology
The integration of XAI with machine learning and deep learning technologies has markedly advanced the field of solar power generation. The proposed SPXAI model effectively tackles
Hybrid machine learning model combining of CNN-LSTM-RF for
The findings highlight the effectiveness of the hybrid machine learning model in accurately forecasting solar power generation. Future research directions could include
Artificial intelligence based hybrid solar energy
This study proposes a hybrid solar power system aided by AI that incorporates high-performance solar tracking, intelligent PV technologies,
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