Parameter Estimation of Chaotic Systems Using Fireworks Algorithm

Li, Hao; Bai, Peng; Xue, Junjie; Zhu, Jie; Zhang, Hui

doi:10.1007/978-3-319-20472-7_49

Cited by 9 publications

(6 citation statements)

References 22 publications

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“…Various practical problems of optimization have been resolved by utilizing FWA such as the design for digital filters, 7 decomposition of a non-negative matrix, 8 parameter optimization for detecting spam, 9 reconfiguration of networks, 10 mass minimization of trusses, 11 parameter estimation of chaotic systems, 12 and multi-satellite control. 13 However, the FWA approach has drawbacks.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED: Dynamic search fireworks algorithm with chaos

Gong

2019

Journal of Algorithms & Computational Technology

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As a relatively new algorithm for swarm intelligence, fireworks algorithm imitates the explosion process of fireworks. A different amplitude in dynamic search fireworks algorithm is presented for an improvement of enhanced fireworks algorithm. This paper integrates chaos with the dynamic search fireworks algorithm so as to further improve the performance and achieve global optimization. Three different variants of dynamic search fireworks algorithm with chaos are introduced and 10 chaotic maps are used to tune either the amplification coefficient C a or the reduction coefficient C r. Twelve benchmark functions are verified in use of the dynamic search fireworks algorithm with chaos (dynamic search fireworks algorithm). The dynamic search fireworks algorithm significantly outperformed the Fireworks Algorithm, enhanced fireworks algorithm, and dynamic search fireworks algorithm based on solution accuracy. The highest performance was seen when dynamic search fireworks algorithm was used with a Gauss/mouse map to tune Ca. Additionally, the dynamic search fireworks algorithm was compared with the firefly algorithm, harmony search, bat algorithm, and standard particle swarm optimization (SPSO2011). Study results indicated that the dynamic search fireworks algorithm has the highest accuracy solution among the five algorithms.

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Section: Introductionmentioning

confidence: 99%

RETRACTED: Dynamic search fireworks algorithm with chaos

Gong

2019

Journal of Algorithms & Computational Technology

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“…To assess the performance of IFWA, it is compared with FWA [8], EFWA [10], dynFWA [12] and SPSO2011 [22].…”

Section: Simulation Results and Analysismentioning

confidence: 99%

“…Inspired by real fireworks, the main idea of the FWA is to use the explosion of the fireworks to search the feasible space of the optimization function, which is a brand new search manner. At present, the fireworks algorithm has been applied to many practical optimization problems [2], the application areas include the factorization of a non-negative matrix [3], the design of digital filters [4], the parameter optimization for the detection of spam [5], the reconfiguration of networks [6], the mass minimization of trusses [7], the parameter estimation of chaotic systems [8], the scheduling of multi-satellite control resources [9], etc.…”

Section: Introductionmentioning

confidence: 99%

Analysis and Improvement of Fireworks Algorithm

Han

Cheng

2017

Algorithms

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Abstract:The Fireworks Algorithm is a recently developed swarm intelligence algorithm to simulate the explosion process of fireworks. Based on the analysis of each operator of Fireworks Algorithm (FWA), this paper improves the FWA and proves that the improved algorithm converges to the global optimal solution with probability 1. The proposed algorithm improves the goal of further boosting performance and achieving global optimization where mainly include the following strategies. Firstly using the opposition-based learning initialization population. Secondly a new explosion amplitude mechanism for the optimal firework is proposed. In addition, the adaptive t-distribution mutation for non-optimal individuals and elite opposition-based learning for the optimal individual are used. Finally, a new selection strategy, namely Disruptive Selection, is proposed to reduce the running time of the algorithm compared with FWA. In our simulation, we apply the CEC2013 standard functions and compare the proposed algorithm (IFWA) with SPSO2011, FWA, EFWA and dynFWA. The results show that the proposed algorithm has better overall performance on the test functions.

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“…Parameter estimation techniques are most commonly used in chaotic systems for demodulating the information signal. Different adapting filtering techniques based on the different chaotic systems used and different conditions such as least mean square (LMS), improved least squares (ILS), recursive least square (RLS) and extended Kalman filter (EKF) have been developed to estimate and track the parameters of chaotic signals [9][10][11]. The tracking and estimation capabilities of these techniques made them suitable for parameter estimation problems and demodulating the information signal in a real time communication system.…”

mentioning

confidence: 99%

Design of Chaotic Bifurcation Parameter Modulation Scheme using Mean Value Estimation

Abdullah

Ali²

2018

Iraqi Journal of ICT

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In this paper, the bifurcation parameter of the chaotic map is estimated accurately by utilizing the ergodic properties of a chaotic dynamical signal. Binary Phase Shift Keying Ergodic Chaotic Parameter Modulation (BPSK-ECPM) scheme is used to modulate the information signal in the bifurcating parameter of the chaotic map. A mean value estimation technique is used at the receiver to retrieve the original information accurately. This method minimizes the computational complexity of the receiver; thereby, reduces the total manufacturing cost. Simulation results confirm that, in AWGN channel and at bit error rate (BER) of 10-3, BPSK-ECPM achieves gains in Eb/N0 of about 0.7dB and 5dB in comparison with conventional direct sequence spread spectrum with BPSK modulation (DS-SS BPSK) and conventional ergodic chaotic parameter modulation spread spectrum (ECPM-SS) systems respectively. The results also confirm that in Rayleigh fading channel and at BER of 10-3, BPSK-ECPM achieves gains in Eb/N0 of about 6.3dB and 1.6dB in comparison with DS-SS BPSK and ECPM-SS systems respectively, which make BPSK-ECPM an ideal candidate for the intelligent transportation system (ITS).

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Parameter Estimation of Chaotic Systems Using Fireworks Algorithm

Cited by 9 publications

References 22 publications

RETRACTED: Dynamic search fireworks algorithm with chaos

RETRACTED: Dynamic search fireworks algorithm with chaos

Analysis and Improvement of Fireworks Algorithm

Design of Chaotic Bifurcation Parameter Modulation Scheme using Mean Value Estimation

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