The ECA-NM hybrid optimization produces chemical-diffusive models that reproduce major flame and detonation properties from detailed chemistry while cutting global error by four orders of magnitude and computational cost by two orders relative to genetic algorithms.
A New Evolutionary Optimization Method Based on Center of Mass
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
EQC claims remain insufficient to surpass state-of-the-art classical algorithms despite embracing decoherence.
citing papers explorer
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An efficient method based on the evolutionary center algorithm for optimizing chemical-diffusive models for flame acceleration and DDT
The ECA-NM hybrid optimization produces chemical-diffusive models that reproduce major flame and detonation properties from detailed chemistry while cutting global error by four orders of magnitude and computational cost by two orders relative to genetic algorithms.
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A Critical Comment on 'Entropy Computing: A Paradigm for Optimization in Open Photonic Systems'
EQC claims remain insufficient to surpass state-of-the-art classical algorithms despite embracing decoherence.