AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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A heterogeneous population co-evolutionary algorithm (HPCEA) tailored for sparse LSMOPs is proposed, and extensive experiments against six state-of-the-art algorithms across eight benchmark suites and three real-world scenarios demonstrate HPCEA’s superiority.
A novel method for the Search and Optimization of IoT Service Composition towards QoS and Energy balance (SOISC-QE) is proposed and an enhanced Dung Beetle Optimization (DBO) is designed by integrating two complementary mechanisms.
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