CAJ | 학술논문

提出一种混沌差分进化和动态逃逸粒子群的节点选择优化算法，通过混沌序列的均匀遍历特性和差分进化算法的高效全局搜索能力，对传感网络中的节点能量进行分类搜索，采用Logistics混沌映射对节点进行优化分区处理，将混沌扰动量融入节点能量分区过程中，获取最佳能量节点，利用动态逃逸粒子群方法，运算无线传感网络最佳能量节点的最优位置，实现网络节点覆盖优化。仿真结果说明，所提算法可增强无线传感网络最优节点的聚类性能，具有更好的无线传感器网络动态节点选择性能，并且收敛速度快，运算耗时少。
제출일충혼돈차분진화화동태도일입자군적절점선택우화산법，통과혼돈서렬적균균편력특성화차분진화산법적고효전국수색능력，대전감망락중적절점능량진행분류수색，채용Logistics혼돈영사대절점진행우화분구처리，장혼돈우동량융입절점능량분구과정중，획취최가능량절점，이용동태도일입자군방법，운산무선전감망락최가능량절점적최우위치，실현망락절점복개우화。방진결과설명，소제산법가증강무선전감망락최우절점적취류성능，구유경호적무선전감기망락동태절점선택성능，병차수렴속도쾌，운산모시소。
A chaos differential evolution and dynamic node selection of particle swarm optimization algorithm, through the chaotic sequence traversal features and efficient global searching ability of differential evolution algorithm, the sensor nodes in a network of energy to search classification, optimize the node partition using Logistics chaos mapping process, blend in chaos disturbance quantity node energy partition in the process, get the best energy node, using the method of dynamic escape particle swarm, optimal operation best energy wireless sensor network node location, optimized network nodes covered. The simulation result shows that the proposed algorithm can enhance the optimal node of wireless sensor network clustering performance, has better performance of wireless sensor network (WSN) dynamic node selection, and fast convergence speed, less operation time.