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Erschienen in:
Recent Advances in Computational Intelligence in Defense and Security Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

mspMEA: The Microcones Separation Parallel Multiobjective Evolutionary Algorithm and Its Application to Fuzzy Rule-Based Ship Classification

verfasst von : Marco Cococcioni

Erschienen in: Recent Advances in Computational Intelligence in Defense and Security

Verlag: Springer International Publishing

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Abstract

This chapter presents a new parallel multiobjective evolutionary algorithm, based on the island model, where the objective space is exploited to distribute the individuals among the processors. The algorithm, which generalizes the well-known cone separation method, mitigates most of its drawbacks. The new algorithm has been employed to speed-up the optimization of fuzzy rule-based classifiers. The fuzzy classifiers are used to build an emulator of the Ship Classification Unit (SCU) contained in modern influence mines. Having an accurate emulator of a mine’s SCU is helpful when needing: (i) to accurately evaluate the risk of traversal of a mined region by vessels/AUVs, (ii) to assess the improvements of ship signature balancing processes, and (iii) to support in-vehicle decision making in autonomous unmanned mine disposal.

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Vorheriges Kapitel Game Theoretical Approach for Dynamic Active Patrolling in a Counter-Piracy Framework
Nächstes Kapitel Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) Using Fuzzy Co-occurrence Matrix Texture Features
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Metadaten
Titel
mspMEA: The Microcones Separation Parallel Multiobjective Evolutionary Algorithm and Its Application to Fuzzy Rule-Based Ship Classification
verfasst von
Marco Cococcioni
Copyright-Jahr
2016
Buch
Recent Advances in Computational Intelligence in Defense and Security

Print ISBN: 978-3-319-26448-6

Electronic ISBN: 978-3-319-26450-9

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-26450-9_17

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