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An improved differential evolution for parameter optimisation

Authors: Xiuqin Pan; Ruixiang Li;

An improved differential evolution for parameter optimisation

Abstract

In this paper, we propose an improved differential evolution DE to solve parameter optimisation problems. The new approach is called ICBBDE, which is an enhanced version of bare bones DE BBDE. The ICBBDE employs an adaptive strategy to dynamically adjust the crossover rate. Moreover, a Cauchy mutation is used to improve the exploration ability. Experiments are conducted on a set of benchmark functions and two real-world parameter optimisation problems. Simulation results demonstrate the efficiency and effectiveness of our approach.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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