Chaotic behavior can be observed in continuous and discrete-time systems.This behavior can appear in one-dimensional nonlinear maps;however,having at least three state variables in flows is necessary.Due to the lower ...Chaotic behavior can be observed in continuous and discrete-time systems.This behavior can appear in one-dimensional nonlinear maps;however,having at least three state variables in flows is necessary.Due to the lower mathematical complexity and computational cost of maps,lots of research has been conducted based on them.This paper aims to present a novel one-dimensional trigonometric chaotic map that is multi-stable and can act attractively.The proposed chaotic map is first analyzed using a single sinusoidal function;then,its abilities are expanded to a map with a combination of two sinusoidal functions.The stability conditions of both maps are investigated,and their different behaviors are validated through time series,state space,and cobweb diagrams.Eventually,the influence of parameter variations on the maps’outputs is examined by one-dimensional and two-dimensional bifurcation diagrams and Lyapunov exponent spectra.Besides,the diversity of outputs with varying initial conditions reveals this map’s multi-stability.The newly designed chaotic map can be employed in encryption applications.展开更多
To enable optimal navigation for unmanned surface vehicle(USV),we proposed an adaptive hybrid strategy-based sparrow search algorithm(SSA)for efficient and reliable path planning.The proposed method began by enhancing...To enable optimal navigation for unmanned surface vehicle(USV),we proposed an adaptive hybrid strategy-based sparrow search algorithm(SSA)for efficient and reliable path planning.The proposed method began by enhancing the fitness function to comprehensively account for critical path planning metrics,including path length,turning angle,and navigation safety.To improve search diversity and effectively avoid premature convergence to local optima,chaotic mapping was employed during the population initialization stage,allowing the algorithm to explore a wider solution space from the outset.A reverse inertia weight mechanism was introduced to dynamically balance exploration and exploitation across different iterations.The adaptive adjustment of the inertia weight further improved convergence efficiency and enhanced global optimization performance.In addition,a Cauchy-Gaussian hybrid update strategy was incorporated to inject randomness and variation into the search process,which helped the algorithm escape local minima and maintain a high level of solution diversity.This approach significantly enhanced the robustness and adaptability of the optimization process.Simulation experiments confirmed that the improved SSA consistently outperformed benchmark algorithms such as the original SSA,PSO,and WMR-SSA.Compared with the three algorithms,in the simulated sea area,the path lengths of the proposed algorithm are reduced by 21%,21%,and 16%,respectively,and under the actual sea simulation conditions,the path lengths are reduced by 13%,15%,and 11%,respectively.The results highlighted the effectiveness and practicality of the proposed method,providing an effective solution for intelligent and autonomous USV navigation in complex ocean environments.展开更多
基金funded by the Centre for Nonlinear Systems,Chennai Institute of Technology,India[grant number CIT/CNS/2023/RP/008].
文摘Chaotic behavior can be observed in continuous and discrete-time systems.This behavior can appear in one-dimensional nonlinear maps;however,having at least three state variables in flows is necessary.Due to the lower mathematical complexity and computational cost of maps,lots of research has been conducted based on them.This paper aims to present a novel one-dimensional trigonometric chaotic map that is multi-stable and can act attractively.The proposed chaotic map is first analyzed using a single sinusoidal function;then,its abilities are expanded to a map with a combination of two sinusoidal functions.The stability conditions of both maps are investigated,and their different behaviors are validated through time series,state space,and cobweb diagrams.Eventually,the influence of parameter variations on the maps’outputs is examined by one-dimensional and two-dimensional bifurcation diagrams and Lyapunov exponent spectra.Besides,the diversity of outputs with varying initial conditions reveals this map’s multi-stability.The newly designed chaotic map can be employed in encryption applications.
基金supported by Shandong Provincial Department of Science and Technology Project(No.2022C01246)National Undergraduate Innovation Training Project(Nos.202410390028,202310390026)+1 种基金Fujian Provincial Undergraduate Innovation Training Project(No.202410390093)Jimei University Innovation Training Project(Nos.2024xj224,2023xj179).
文摘To enable optimal navigation for unmanned surface vehicle(USV),we proposed an adaptive hybrid strategy-based sparrow search algorithm(SSA)for efficient and reliable path planning.The proposed method began by enhancing the fitness function to comprehensively account for critical path planning metrics,including path length,turning angle,and navigation safety.To improve search diversity and effectively avoid premature convergence to local optima,chaotic mapping was employed during the population initialization stage,allowing the algorithm to explore a wider solution space from the outset.A reverse inertia weight mechanism was introduced to dynamically balance exploration and exploitation across different iterations.The adaptive adjustment of the inertia weight further improved convergence efficiency and enhanced global optimization performance.In addition,a Cauchy-Gaussian hybrid update strategy was incorporated to inject randomness and variation into the search process,which helped the algorithm escape local minima and maintain a high level of solution diversity.This approach significantly enhanced the robustness and adaptability of the optimization process.Simulation experiments confirmed that the improved SSA consistently outperformed benchmark algorithms such as the original SSA,PSO,and WMR-SSA.Compared with the three algorithms,in the simulated sea area,the path lengths of the proposed algorithm are reduced by 21%,21%,and 16%,respectively,and under the actual sea simulation conditions,the path lengths are reduced by 13%,15%,and 11%,respectively.The results highlighted the effectiveness and practicality of the proposed method,providing an effective solution for intelligent and autonomous USV navigation in complex ocean environments.
