科技通报
科技通報
과기통보
BULLETIN OF SCIENCE AND TECHNOLOGY
2015年
5期
179-183
,共5页
汽车电子节点%负载%布谷鸟算法%高斯变异%反向学习多样性
汽車電子節點%負載%佈穀鳥算法%高斯變異%反嚮學習多樣性
기차전자절점%부재%포곡조산법%고사변이%반향학습다양성
automobile electronic node%load%cuckoo algorithm%Gaussian mutation%diversity of reverse learning
汽车电子节点负载一直都是汽车电子系统中的研究重点，本文针对汽车电子任务负载不均衡的特点，引入布谷鸟算法，在该算法的基础引入高斯变异算子来处理每一个阶段中的鸟窝最佳位置的选择，然后通过反向学习的多样性因子对不同阶段中的鸟窝位置进行调整，通过改进后的算法使得寻找最优解的效率得到了提高。仿真实验证明本文算法在一定程度上提高汽车电子节点的任务资源分配效率，降低了节点资源分配的消耗。
汽車電子節點負載一直都是汽車電子繫統中的研究重點，本文針對汽車電子任務負載不均衡的特點，引入佈穀鳥算法，在該算法的基礎引入高斯變異算子來處理每一箇階段中的鳥窩最佳位置的選擇，然後通過反嚮學習的多樣性因子對不同階段中的鳥窩位置進行調整，通過改進後的算法使得尋找最優解的效率得到瞭提高。倣真實驗證明本文算法在一定程度上提高汽車電子節點的任務資源分配效率，降低瞭節點資源分配的消耗。
기차전자절점부재일직도시기차전자계통중적연구중점，본문침대기차전자임무부재불균형적특점，인입포곡조산법，재해산법적기출인입고사변이산자래처리매일개계단중적조와최가위치적선택，연후통과반향학습적다양성인자대불동계단중적조와위치진행조정，통과개진후적산법사득심조최우해적효솔득도료제고。방진실험증명본문산법재일정정도상제고기차전자절점적임무자원분배효솔，강저료절점자원분배적소모。
Automobile electronic node load has always been the research focus in automobile electronic system. According to the automobile electronic task’s characteristics of imbalanced load, the author of this paper has introduced the cuckoo algorithm, based on which Gaussian mutation operator is introduced to select the optimal location of bird’s nest at every stage, then adjust the nest’s location at different stages through the diversity factor of reverse learning, and improve the efficiency of finding optimal solutions through the improved algorithm. Simulation experiments have proved that the algorithm proposed in this paper has to some extent improved the automobile electronic node’s efficiency of task resources allocation and reduced its consumption in resources allocation.
