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针对不确定环境下无线传感器网络覆盖能效优化问题,提出一种传感器节点区间感知模型;进而考虑网络覆盖率和节点冗余率,将其转化为区间多目标优化问题.基于一种新型区间个体依可能度占优关系,提出区间多目标量子文化算法,根据区间占优个体信息提取隐含知识,用于指导量子个体更新及进化个体变异与选择.不同环境下的仿真结果表明:基于所提出算法获得的Pareto解具有更好的收敛性、分布性和延展性;相应的无线传感器网络布局更合理.
Aiming at the energy efficiency optimization of wireless sensor network coverage in uncertain environment, a sensor node interval awareness model is proposed, and then the network coverage rate and node redundancy rate are considered to convert it into interval multi-objective optimization problem.Based on a new interval individual, Probability and dominative relationship, the interval multi-objective quantum culture algorithm is proposed, and implicit knowledge is extracted according to dominance-based interval information to guide the update and evolution of individual individuals. The simulation results under different environments show that based on the proposed algorithm The obtained Pareto solution has better convergence, distribution and scalability; the corresponding wireless sensor network layout is more reasonable.