摘要
将遗传算法进行改进并应用于无线传感网络的优化设计中,根据森林的实际环境建立合适的数学模型,并在此基础上给出适应度函数和传感器网络的组网策略。当有异常情况发生,能够准确及时的发出警报,并发出位置信息。针对遗传算法容易进入局部最优解的误区,把模拟退火算子加入遗传算法,同时基于以往的交叉概率和遗传概率的选取不当给寻优结果带来的很大影响,本文在寻优过程中动态的调整了交叉概率和变异概率。MATLAB仿真结果表明:改进的遗传算法提高了算法的寻优速度,克服了局部收敛的误区,优化了无线传感网络的能量使网络的生命周期达到最长。
The genetic algorithm was improved and applied to the optimization design of wireless sensor network,according to the actual environment of forest to establish an appropriate mathematical model,and on this basis the fitness function and the sensor network strategy was given.When anomalies occur,this algorithm can accurately and timely issue alerts and position information.For the genetic algorithm is easy to enter the errors of the local optimal solution,the simulated annealing operator join in the genetic algorithm,also based on the past,selected Crossover probability and Genetic probability of improperly,brought a significant impact to the optimization results,in this paper,in the optimization process dynamically adjust the crossover probability and mutation probability.MATLAB simulation results show that the improved genetic algorithm improved Algorithm optimization speed,overcome the local convergence of the errors,optimized Wireless sensor networks energy to achieve the longest life cycle of the network.
出处
《计算机系统应用》
2011年第5期130-134,共5页
Computer Systems & Applications
关键词
遗传算法
无线传感网络
适应度函数
网络优化
genetic algorithms
wireless sensor networks
fitness function
network optimization
