改进的遗传优化算法在节点定位中的应用

摘要

Aiming at the problem of low positioning accuracy of the wireless sensor networks algorithm, a new kind of algorithm (GADO, dynamization optimization and genetic algorithm) is proposed. The algorithm combines the dynamical evolutionary algorithm with the iterative optimization in the genetic algorithm. Comparing with the classical DV-hop localization algorithm and genetic algorithm, using GADO algorithm to solve the network beacon nodes, the positioning error is obviously reduced, and the precision is better.%针对无线传感器网络算法定位精度不高的问题，提出一种定位算法（GADO），该算法将动力学中进化计算和遗传算法中迭代优选相结合。用GADO算法求解网络信标节点与经典的DV-hop定位算法、遗传算法进行对比，改进的算法定位误差明显减少，精度更好。