Architecture of hybrid CNN-LSTM.

Architecture of hybrid CNN-LSTM.

<p>This figure illustrates the hybrid CNN-LSTM model architecture for processing spatial and temporal data.</p>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Yousef Sanjalawe (22216626) (author)
مؤلفون آخرون:	Salam Fraihat (22216629) (author), Salam Al-E’mari (22216632) (author), Mosleh Abualhaj (22216635) (author), Sharif Makhadmeh (22216638) (author), Emran Alzubi (22216641) (author)
منشور في:	2025
الموضوعات:	Medicine Evolutionary Biology Ecology Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified yielding notable improvements modern technological infrastructures introduced significant challenges integrating feature selection integrates feature selection heightened operational costs extensive simulations conducted deep learning models advanced techniques offers world dataset called particle swarm optimization optimizing resource allocation novel smart load dynamic task scheduling suboptimal resource utilization smart load balancing feature selection algorithms div >< p deep reinforcement learning efficient load balancing resource utilization traditional load resource management optimization approach load prediction hybrid load handling dynamic efficient approach dataset reveal balancing methodology balancing approaches workload management term memory sladro </ pso )— paper proposes paper presents long short increasing dependence hybrid bio fluctuating workloads energy efficiency critical need comprehensive framework complex nature cloud environments cloud computing
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