文件名称：Rotated Whale Optimization Algorithm
文件大小：1.92MB
文件格式：ZIP
更新时间：2024-07-28 04:58:14
计算机
Algorithm Updated 2 minutes ago Wireless sensor network(WSN) attracts the attention of more and more researchers and it is applied in more and more environments. The localization information is one of the most important information in WSN. This pape proposed a novel algorithm called the rotated black hole(RBH) algorithm, which introduces a rotated optimal path and greatly improves the global search ability of the original black hole(BH) algorithm. Then, the novel algorithm is applied in reducing the localization error ofWSN in 3D terrain. CEC 2013 test suit is used to verify the performance of the novel algorithm, and the simulation results show the novel algorithm has better search performance than other famous intelligence computing algorithms. The localization simulation experiment results reveal the novel algorithm also has an excellent performance in solving practical problems.
【文件预览】：
代码
----Distance.m(221B)
----DV_Hop_BH.m(1KB)
----400nodes.mat(6KB)
----GA.m(1KB)
----Dvhop.m(5KB)
----DV_Hop_WOA.m(3KB)
----WOA.m(3KB)
----main.m(765B)
----300nodes.mat(5KB)
----350nodes.mat(5KB)
----450nodes.mat(7KB)
----BH.m(1KB)
----input_data()
--------M_D20.txt(98KB)
--------M_D10.txt(25KB)
--------M_D50.txt(611KB)
--------M_D80.txt(1.53MB)
--------M_D100.txt(2.39MB)
--------M_D70.txt(1.17MB)
--------M_D90.txt(1.93MB)
--------M_D5.txt(6KB)
--------M_D60.txt(880KB)
--------shift_data.txt(24KB)
--------M_D30.txt(220KB)
--------M_D2.txt(1KB)
--------M_D40.txt(391KB)
----coordinate.mat(76KB)
----fun_w.m(525B)
----数据.xlsx(80KB)
----200nodes.mat(5KB)
----DV_Hop_GA.m(2KB)
----cec13_func.mexw64(37KB)
----DV_Hop_PSO.m(2KB)
----Dist.m(189B)
----DV_Hop_RBH.m(1KB)
----500nodes.mat(8KB)
----250nodes.mat(4KB)
----cec13_func.cpp(26KB)
----PSO.m(2KB)
----Rotate_BH.m(1KB)
----DV_Hop_RBH.asv(1KB)