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Titlebook: Bio-Inspired Computing: Theories and Applications; 16th International C Linqiang Pan,Zhihua Cui,Lianghao Li Conference proceedings 2022 Spr

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Bio-Inspired Computing: Theories and Applications978-981-19-1256-6Series ISSN 1865-0929 Series E-ISSN 1865-0937
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Die Gewinnung von Fichtensamen betr,ortance of picking stations, which affects the efficiency of the system, is often ignored. To tackle this problem, this study has designed a novel scheduling model to improve the efficiency of the multi-robot system. Unlike the original scheduling model, the queuing time is taken into account in the
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https://doi.org/10.1007/978-3-642-94230-3nergy balance problem becoming more and more prominent. To meet this challenge, a multi-objective wireless sensor network energy balance model is described, which comprehensively considers the energy consumption of sensor node and neighbor node, sensor node and base station. Meanwhile, an improved m
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https://doi.org/10.1007/978-3-662-37977-6works do not require preset base stations and are suitable for special scenarios such as rapid networking on the battlefields and post-disaster rescues. The distance vector-based AODV routing protocol is an on-demand routing protocol specially developed for Ad Hoc networks. Due to the simplicity of
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https://doi.org/10.1007/978-3-7091-9374-7istics. The artificial bee colony algorithm (ABC) is one of the popular evolutionary algorithms to solve large-scale scheduling problems. A new artificial bee colony algorithm is proposed, named the learning-based artificial bee colony algorithm (LB-ABC). We proposed two new learning strategies, nam
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L. H. Eckensberger,R. Kreibich-Fischer can quickly search for feature subsets, effectively reducing the computational workload; However, in some decision tables of this type of method, there were also problems such as the searched feature subset containing redundant features, which led to a decrease in accuracy. Aiming at such problems
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