Performance of hybrid CNN-LSTM model with various feature selection techniques.

Performance of hybrid CNN-LSTM model with various feature selection techniques.

<p>Performance of hybrid CNN-LSTM model with various feature selection techniques.</p>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Saad Hammood Mohammed (20623506) (author)
مؤلفون آخرون:	Mandeep S. Jit Singh (20623509) (author), Abdulmajeed Al-Jumaily (20623512) (author), Mohammad Tariqul Islam (7854059) (author), Md. Shabiul Islam (20536677) (author), Abdulmajeed M. Alenezi (20623515) (author), Mohamed S. Soliman (17974428) (author)
منشور في:	2025
الموضوعات:	Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified renewable energy sources reducing false positives minimizing false negatives introduced numerous benefits inspired optimization algorithms industrial control system improving computational efficiency grey wolf optimization fewer unnecessary interventions experimental results demonstrate deep learning classifiers also increased vulnerability smart grid environment often fall short power system dataset hybrid ids framework existing ids techniques reliable detection system hybrid feature selection including enhanced efficiency cyber attack dataset measure balances recall smart grids reliable operation long short detection performance cyber threats attack types dataset used novel ids ids employs time processing term memory temporal features study presents scalability challenges relevant features predefined rules paper addresses main objective key metrics integrating real including accuracy future research fdias ). detecting fdias detect fdias
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