Lévy flight and chaos theory based gravitational search algorithm for multilayer perceptron training

Rather, Sajad Ahmad; Bala, P. Shanthi

doi:10.1007/s12530-022-09456-y

Cited by 6 publications

(1 citation statement)

References 65 publications

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“…Compared with other chaotic mappings, Tent chaotic mapping [21] shows great advantages in ergodicity. Ergodicity means that the algorithm can comprehensively explore the solution space, thereby increasing the possibility of finding the global optimal solution.…”

Section: An Improved Seagull Optimization Algorithm Incorporating Ten...mentioning

confidence: 99%

A Tent-Lévy-Based Seagull Optimization Algorithm for the Multi-UAV Collaborative Task Allocation Problem

Zhou,

Liu,

Dai

et al. 2024

Applied Sciences

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With the rapid advancement of unmanned aerial vehicle technology, the extensive application of multiple unmanned aerial vehicle systems in agriculture has led to significant innovations and benefits. Addressing the challenge of task allocation for multiple unmanned aerial vehicles, the primary objective is to minimize the total time required for unmanned aerial vehicles to return to their starting point after task completion. To tackle this issue, a mathematical model for the multi-constrained multiple unmanned aerial vehicle collaborative task allocation problem is developed. To efficiently solve this model, we propose an enhanced Seagull Optimization Algorithm, which integrates the Tent chaotic mapping strategy and the Lévy flight strategy. The Tent chaotic mapping helps the algorithm avoid becoming trapped in local optima, while the Lévy flight strategy, employed during the seagull attack phase, enhances the algorithm’s diversity and its ability to escape local optima. Additionally, the spiral coefficient is refined to balance the coordination between global and local searches. Simulation experiments demonstrate that the proposed algorithm can swiftly and effectively identify a reasonable task allocation scheme for solving the multi-constrained multi-UAV collaborative task allocation problem.

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Section: An Improved Seagull Optimization Algorithm Incorporating Ten...mentioning

confidence: 99%

A Tent-Lévy-Based Seagull Optimization Algorithm for the Multi-UAV Collaborative Task Allocation Problem

Zhou,

Liu,

Dai

et al. 2024

Applied Sciences

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show abstract

Improving the Generalisation Ability of Neural Networks Using a Lévy Flight Distribution Algorithm for Classification Problems

Bojnordi¹,

Mousavirad

Pedram

et al. 2023

New Gener. Comput.

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COVID-19 chest CT scan image segmentation based on chaotic gravitational search algorithm

Rather,

Das,

Çiftçioğlu

2024

Evolving Systems

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Lévy flight and chaos theory based gravitational search algorithm for multilayer perceptron training

Cited by 6 publications

References 65 publications

A Tent-Lévy-Based Seagull Optimization Algorithm for the Multi-UAV Collaborative Task Allocation Problem

A Tent-Lévy-Based Seagull Optimization Algorithm for the Multi-UAV Collaborative Task Allocation Problem

Improving the Generalisation Ability of Neural Networks Using a Lévy Flight Distribution Algorithm for Classification Problems

COVID-19 chest CT scan image segmentation based on chaotic gravitational search algorithm

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