A hopfield neural network algorithm for automatic name placement for point feature

This paper presents a method of adding label to the map especially for the point feature. This method overcomes the shortcoming of traditional methods, e.g.Conflict-Backtracking method. Its kernel algorithm use the hopfield neural network to find the best label position for point feature. The experimental resuits proves that this algorithm has good permanence and high speed.     

A hopfield neural network algorithm for automatic name placement for point feature

This paper presents a method of adding label to the map especially for the point feature. This method overcomes the shortcoming of traditional methods, e.g. Conflict-Backtracking method. Its kernel algorithm use the hopfield neural network to find the best label position for point feature. The experimental results proves that this algorithm has good permanence and high speed.     

基于遗传算法的点状要素注记的整体最优配置

提出了一种点状要素自动注记的整体最优解的解决方案,其核心算法采用具有全局搜索特性的遗传算法,可以获取点状要素注记配置的(近似)全局最优解。