The rapiddevelopment of the global shipping industry and the changes in complex marine environments have put forward higher requirements for ship formation and route optimization. The purpose of the research is to im...
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The rapiddevelopment of the global shipping industry and the changes in complex marine environments have put forward higher requirements for ship formation and route optimization. The purpose of the research is to improve the efficiency and accuracy of ship formation and route planning through improvedalgorithms. Based on this, a ship formation model combining improvedparticle swarm optimization algorithm and a generative route optimization method based on improveddouglas-peucker algorithm are proposed. The particle swarm algorithm introduces dynamic adaptive parameter adjustment and the cross mutation strategy of genetic algorithm, while the douglas-peucker algorithm integrates density-based noise application spatial clustering algorithm to improve model performance. The test results show that the total navigation distance of the allocation path generated by the ship formation model is 605.3 meters, the calculation time is 31.8 seconds, and all ships can be accurately allocated to the target point. When the number of iterations is 1000, the route optimization model has a route coverage rate of 95.9% on the training set, an average error of 30.5 meters, and a computation time of 45.9 seconds, achieving zero collisions. The experimental results show that the improvedalgorithm outperforms traditional methods in accuracy and stability of formation target allocation and route planning, especially under complex sea conditions, and can significantly reduce computation time and errors. The research provides a new technological means for optimizing ship formations and routes, which has certain application potential andpractical value.
In today's global sports arena, tennis has undoubtedly become a highly focused andpopular event. With deepening analysis of tennis techniques, especially the detailed study of the ball-striking mechanism, coaches...
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In this paper, a new recognition algorithm was developed based on the skin color model and the fingertip structure detection to improve the hand gesture recognition accuracy based on the traditional Hu's moment fe...
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In this paper, a new recognition algorithm was developed based on the skin color model and the fingertip structure detection to improve the hand gesture recognition accuracy based on the traditional Hu's moment features. Firstly, the geometric features and the areas of skin were adopted to segment the skin region from the background. The douglas-peucker (d-p) algorithm was utilized to conduct the contour approximation to get a polygonal in the process of feature detection. Then the convexity point inspections were conducted in the polygonal. Secondly, we developed two rules for locating and numbering the fingertips. After that, we built a seven-dimensional feature vector. Finally, the hand gesture was recognized by using the distance matching criterion. The developed recognition algorithm improved the recognition accuracy by 2.7% compared with the traditional Hu's moment features. Additionally, it has good robustness in several manners such as shifting, plane rotation and scaling.
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