Chaotic-based hybrid negative selection algorithm and its applications in fault and anomaly detection

Aydın, İlhan; Karaköse, Mehmet; Akın, Erhan

doi:10.1016/j.eswa.2010.01.011

Cited by 74 publications

(31 citation statements)

References 25 publications

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“…Although a number of DE variants have been recently developed, the focus of this paper is the further development of ChaosDE concept, which is based on the embedding of chaotic systems in the form of Chaos Pseudo Random Number Generators (CPRNG) into the DE. A chaotic approach generally uses the discrete chaotic map as a pseudo random number generator [2]. This causes the meta-heuristic to map unique regions, since the discrete chaotic map iterates to new regions.…”

Section: Introductionmentioning

confidence: 99%

An Initial Study on the New Adaptive Approach for Multi-chaotic Differential Evolution

Šenkeřík

Pluháček

Oplatková

2015

Advances in Intelligent Systems and Computing

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Abstract. This paper aims on the initial investigations on the novel adaptive multi-chaos-driven evolutionary algorithm Differential Evolution (DE). This paper is focused on the embedding and adaptive alternating of set of two discrete dissipative chaotic systems in the form of chaotic pseudo random number generators for the DE. In this paper the novel adaptive concept of DE/rand/1/bin strategy driven alternately by two chaotic maps (systems) is introduced. Repeated simulations were performed and analyzed on the well known test function in higher dimension setting.

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Section: Introductionmentioning

confidence: 99%

An Initial Study on the New Adaptive Approach for Multi-chaotic Differential Evolution

Šenkeřík

Pluháček

Oplatková

2015

Advances in Intelligent Systems and Computing

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“…As new evidence continuously accumulated SNS was modified twice in 1969 and in 1975. In1969, Bretscher and Cohn added a new cell (T cell) and a new signal (help), proposing that the B cell would die if it recognized antigen in the absence of help [12]. In 1975, Lafferty and Cunningham proposed that T cells also need a second signal (named "costimulation"), which they receive from "stimulator" cells (APCs) [13].…”

Section: Figure 1 Three Important Immunological Modelsmentioning

confidence: 99%

A Fast Immune Recognition Model based on Immune Response

Yuan

Hu²

2014

IJMUE

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“…An evolutionary chaotic approach generally uses the chaotic system in the place of a pseudo random number generator [12]. This causes the heuristic to map unique regions, since the chaotic system iterates to new regions.…”

Section: Motivationmentioning

confidence: 99%

Simulation Of Time-Continuous Chaotic UEDA Oscillator As The Generator Of Random Numbers For Heuristic

Šenkeřík¹,

Pluháček²,

Davendra³

et al. 2015

ECMS 2015 Proceedings Edited By: Valeri M. Mladenov, Petia Georgieva, Grisha Spasov, Galidiya Petrova

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This paper investigates the utilization of the timecontinuous chaotic system, which is UEDA oscillator, as the chaotic pseudo random number generator. (CPRNG). Repeated simulations were performed investigating the influence of the oscillator sampling time to the selected heuristic, which is differential evolution algorithm (DE). Initial experiments were performed on the selected test function in higher dimensions.

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Chaotic-based hybrid negative selection algorithm and its applications in fault and anomaly detection

Cited by 74 publications

References 25 publications

An Initial Study on the New Adaptive Approach for Multi-chaotic Differential Evolution

An Initial Study on the New Adaptive Approach for Multi-chaotic Differential Evolution

A Fast Immune Recognition Model based on Immune Response

Simulation Of Time-Continuous Chaotic UEDA Oscillator As The Generator Of Random Numbers For Heuristic

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