LSTM performance and results before optimization.

<div><p>This paper proposes a model called X-LSTM-EO, which integrates explainable artificial intelligence (XAI), long short-term memory (LSTM), and equilibrium optimizer (EO) to reliably forecast solar power generation. The LSTM component forecasts power generation rates based on enviro...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Rizk M. Rizk-Allah (18625751) (author)
مؤلفون آخرون:	Lobna M. Abouelmagd (19787120) (author), Ashraf Darwish (19207662) (author), Vaclav Snasel (4489414) (author), Aboul Ella Hassanien (15572857) (author)
منشور في:	2024
الموضوعات:	Genetics Ecology Science Policy Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified smart solar systems power generation patterns photovoltaic power units machine learning algorithm implemented utilizing tensorflow based local interpretable original model ’ eo component optimizes div >< p rmse ), coefficient model called x lstm model ’ proposed x efficiency coefficient proposed model lstm ), eo model term memory simulations demonstrate pso optimizer paper proposes paper improve keras within independent explanation improvement rate gradient boosting five metrics explainable ai equilibrium optimizer eo optimizer environmental conditions employed instead ec respectively ec ). decision tree critical factors conventional lstm abrupt changes
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LSTM performance and results before optimization.

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