计算机工程与设计
計算機工程與設計
계산궤공정여설계
COMPUTER ENGINEERING AND DESIGN
2015年
8期
2108-2113
,共6页
数字散斑相关方法%布谷鸟搜索算法%散斑图%粒子群算法%收敛速度
數字散斑相關方法%佈穀鳥搜索算法%散斑圖%粒子群算法%收斂速度
수자산반상관방법%포곡조수색산법%산반도%입자군산법%수렴속도
digital speckle correlation method%cuckoo search algorithm%specklegram%particle swarm optimization%conver-gence rate
为克服基于传统数字散斑相关方法搜索结果易陷入局部最优、后期收敛速度慢等缺点，引入基于群体智能的布谷鸟搜索算法，从随机步长、鸟巢更新策略和最优鸟巢扰动策略3方面对算法进行改进。以模拟散斑图为研究对象，观察改进布谷鸟搜索算法在相关搜索时鸟巢的运动轨迹，与基本布谷鸟搜索算法、粒子群算法在寻优精度和收敛速度方面进行比较。仿真结果验证了该算法应用于数字散斑相关方法的可行性和优越性。
為剋服基于傳統數字散斑相關方法搜索結果易陷入跼部最優、後期收斂速度慢等缺點，引入基于群體智能的佈穀鳥搜索算法，從隨機步長、鳥巢更新策略和最優鳥巢擾動策略3方麵對算法進行改進。以模擬散斑圖為研究對象，觀察改進佈穀鳥搜索算法在相關搜索時鳥巢的運動軌跡，與基本佈穀鳥搜索算法、粒子群算法在尋優精度和收斂速度方麵進行比較。倣真結果驗證瞭該算法應用于數字散斑相關方法的可行性和優越性。
위극복기우전통수자산반상관방법수색결과역함입국부최우、후기수렴속도만등결점，인입기우군체지능적포곡조수색산법，종수궤보장、조소경신책략화최우조소우동책략3방면대산법진행개진。이모의산반도위연구대상，관찰개진포곡조수색산법재상관수색시조소적운동궤적，여기본포곡조수색산법、입자군산법재심우정도화수렴속도방면진행비교。방진결과험증료해산법응용우수자산반상관방법적가행성화우월성。
To overcome the defects including easily falling into local optimum and slow convergence speed in the later stage of tra-ditional digital speckle correlation method,the cuckoo search algorithm based on swarm intelligence was introduced,and it was improved from three aspects including the random step length,the nest update strategy and the best nest disturbance strategy. Study was pictured to simulate specklegram,the nest trajectory of improved search algorithm cuckoo was observed during the search.The accuracy and convergence speed of the proposed algorithm were compare with that of the basic cuckoo search algo-rithm and particle swarm optimization algorithm.Simulation results show that the algorithm used in digital speckle correlation method is feasible and superior.
