Titlebook: Glowworm Swarm Optimization; Theory, Algorithms, Krishnanand N. Kaipa,Debasish Ghose Book 2017 Springer International Publishing AG 2017 G

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From Natural to Synthetic Swarms,hanisms to congregate into large swarms for the purpose of mass mating. Ants use trail-laying and trail-following behaviors to self-organize into complex foraging patterns; ants gathered in groups can carry prey that are so large that if they were fragmented, the members of the group would be unable

半圆凿

Glowworm Swarm Optimization: Algorithm Development,roduced, which is followed by a description of the phases that constitute each cycle of the algorithm. GSO, in its present form, has evolved out of several significant modifications incorporated into the earlier versions of the algorithm. Many ideas were considered in the development process before

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Applications to Ubiquitous Computing Environments,ion tasks. The basic GSO algorithm, which was applied to multimodal optimization and signal source localization problems, considers a homogeneous swarm of mobile agents. In this chapter, a GSO variant for a heterogeneous swarm of mobile and stationary agents is developed and its application to ubiqu

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Approximate computing: Error Tolerant Adder,ult of addition is been generated but it takes long time to calculate it and also generate much more heat that may damage the components. But in the Error tolerant adder (Approximate Adder) the result of addition is in approximated form but the time of calculation is lesser than before and the proce

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