Comparison between Binary Particles Swarm Optimization (BPSO) and Binary Artificial Bee Colony (BABC) for nonlinear autoregressive model structure selection of chaotic data

Zabidi, Azlee; Yassin, Ihsan Mohd; Tahir, Nooritawati Md; Rizman, Zairi Ismael; Karbasi, Mostafa

doi:10.4314/jfas.v9i3s.57

Cited by 5 publications

(2 citation statements)

References 27 publications

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“…These works conclude that ABC algorithm can converge faster than particle swarm optimization (PSO), genetic algorithm (GA), cuckoo-search, and differential evolution. [38][39][40] Moreover, another work comparison to other full search (FS) methods, modified ABC algorithm (MABCA), outperformed. 40,41 The authors compared MABCA to six FS methods including FS, three-step search, new three-step search, simple and efficient search, four-step search, and diamond search.…”

Section: Related Workmentioning

confidence: 99%

A low-cost solution for unmanned aerial vehicle navigation in a global positioning system–denied environment

Ashraf

Aggarwal²,

Damacharla

et al. 2018

International Journal of Distributed Sensor Networks

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The ability of an autonomous unmanned aerial vehicle to navigate and fly precisely determines its utility and performance. The current navigation systems are highly dependent on the global positioning system and are prone to error because of global positioning system signal outages. However, advancements in onboard processing have enabled inertial navigation algorithms to perform well during short global positioning system outages. In this article, we propose an intelligent optical flow-based algorithm combined with Kalman filters to provide the navigation capability during global positioning system outages and global positioning system-denied environments. Traditional optical flow measurement uses block matching for motion vector calculation that makes the measurement task computationally expensive and slow. We propose the application of an artificial bee colony-based block matching technique for faster optical flow measurements. To effectively fuse optical flow data with inertial sensors output, we employ a modified form of extended Kalman filter. The modifications make the filter less noisy by utilizing the redundancy of sensors. We have achieved an accuracy of 95% for all non-global positioning system navigation during our simulation studies. Our real-world experiments are in agreement with the simulation studies when effects of wind are taken into consideration.

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Section: Related Workmentioning

confidence: 99%

A low-cost solution for unmanned aerial vehicle navigation in a global positioning system–denied environment

Ashraf

Aggarwal²,

Damacharla

et al. 2018

International Journal of Distributed Sensor Networks

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show abstract

“…The results have very slight different with single PSO [30]. In this paper, the composition of a set of implementation frameworks for the LLH of PSO-GA [31] with dynamic parameterization has been presented. The implementation frameworks are developed based on a general taxonomy that classify the common terminology of the LLH.…”

Section: Constant Parameterizationmentioning

confidence: 99%

The implementation frameworks of meta-heuristics hybridization with dynamic parameterization

Masrom

Rahman

Abidin

et al. 2018

J. Fundam and Appl Sci.

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The hybridization of meta-heuristics algorithms has achieved a remarkable improvement from the adaptation of dynamic parameterization. This paper proposes a variety of implementation frameworks for the hybridization of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) and the dynamic parameterization. In this paper, taxonomy of the PSO-GA with dynamic parameterization is presented to provide a common terminology and classification mechanisms. Based on the taxonomy, thirty implementation frameworks are possible to be adapted. Furthermore, different algorithms that used the implementation frameworks with sequential scheme and dynamic parameterizations approaches are tested in solving a facility layout problem.

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A survey on the Artificial Bee Colony algorithm variants for binary, integer and mixed integer programming problems

Akay

Karaboğa

Görkemli

et al. 2021

Applied Soft Computing

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Comparison between Binary Particles Swarm Optimization (BPSO) and Binary Artificial Bee Colony (BABC) for nonlinear autoregressive model structure selection of chaotic data

Cited by 5 publications

References 27 publications

A low-cost solution for unmanned aerial vehicle navigation in a global positioning system–denied environment

A low-cost solution for unmanned aerial vehicle navigation in a global positioning system–denied environment

The implementation frameworks of meta-heuristics hybridization with dynamic parameterization

A survey on the Artificial Bee Colony algorithm variants for binary, integer and mixed integer programming problems

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