• Publications
  • Influence
The (1+λ) evolutionary algorithm with self-adjusting mutation rate
TLDR
We propose a new way to self-adjust the mutation rate in population-based evolutionary algorithms. Expand
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k-Bit Mutation with Self-Adjusting k Outperforms Standard Bit Mutation
TLDR
When using the classic standard bit mutation operator, parent and offspring differ in a random number of bits, distributed according to a binomial law. Expand
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Runtime analysis for self-adaptive mutation rates
TLDR
We propose and analyze a self-adaptive version of the (1, λ) evolutionary algorithm in which the current mutation rate is part of the individual and thus also subject to mutation. Expand
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Optimal Parameter Choices via Precise Black-Box Analysis
TLDR
We prove that the unary unbiased black-box complexity of the classic OneMax function class is cn ± o(n) for a constant c between 0.2539 and 0.2665. Expand
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The ($$1+\lambda $$1+λ) Evolutionary Algorithm with Self-Adjusting Mutation Rate
TLDR
We propose a new way to self-adjust the mutation rate in population-based evolutionary algorithms in discrete search spaces. Expand
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Runtime Analysis for Self-adaptive Mutation Rates
TLDR
We propose and analyze a self-adaptive version of the $$(1,\lambda )$$ ( 1 , λ ) evolutionary algorithm in which the current mutation rate is encoded within the individual and thus also subject to mutation. Expand
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Wind Turbine Clutter Mitigation in Coastal UHF Radar
Coastal UHF radar provides a unique capability to measure the sea surface dynamic parameters and detect small moving targets, by exploiting the low energy loss of electromagnetic waves propagatingExpand
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Parameter Estimation of Double Exponential Pulse Based on Artificial Neural Network
In the study of high-power electromagnetic environments, double exponential function is widely used. The physical parameters of the pulse are the rise time tr and the pulse width tw, which have aExpand
Designing Superior Evolutionary Algorithms via Insights From Black-Box Complexity Theory. (Conception de meilleurs algorithmes évolutionnaires grâce à la théorie de la complexité boîte noire)
  • Jing Yang
  • Mathematics, Computer Science
  • 4 September 2018
TLDR
We prove that the unary unbiased black-box complexity of the OneMax benchmark function class is $n ln(n) - cn pm o( n)$ for a constant $c$ which is between $0.2539$ and $2665$. Expand
Traductologie, linguistique,culture : recherches sur des perspectives interculturelles relatives à l'héritage de l'Europe et de la Chine
En partant d’une synthese sur les relations entre l’evolution de langue, la culture et la traduction, la these vise a etablir une recherche a propos des effets d’influence de la culture d’arrivee surExpand
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