A Comparison between Metaheuristics as Strategies for Minimizing Cyclic Instability in Ambient Intelligence

A Comparison between Metaheuristics as Strategies for Minimizing Cyclic Instability in Ambient Intelligence

In this paper we present a comparison between six novel approaches to the fundamental problem of cyclic instability in Ambient Intelligence. These approaches are based on different optimization algorithms, Particle Swarm Optimization (PSO), Bee Swarm Optimization (BSO), micro Particle Swarm Optimiza...

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Bibliographic Details
Main Authors: Vic Callaghan, Marco Sotelo, Efren Mezura, Rosario Baltazar, Leoncio A. Romero, Victor Zamudio
Format: Article
Language:English
Published: MDPI AG 2012-08-01
Series:Sensors
Subjects:
cyclic instability
ambient intelligence
locking
Online Access:http://www.mdpi.com/1424-8220/12/8/10990

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