计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2013年
8期
58-62
,共5页
李会%张天丽%陶佰睿%王新红
李會%張天麗%陶佰睿%王新紅
리회%장천려%도백예%왕신홍
人工鱼群%群体智能%自适应调整%函数优化
人工魚群%群體智能%自適應調整%函數優化
인공어군%군체지능%자괄응조정%함수우화
artificial fish-swarm%swarm intelligence%adaptive adjustment%function optimization
为了克服基本人工鱼群算法收敛速度慢、求解精度不高和易陷入局部最优的不足,提出了自适应调整人工鱼群算法参数的方法,该方法采用个体鱼适应值与整个鱼群的平均适应值作比较,将整个鱼群分为三组,再采用自适应调整每组鱼群的视野范围和步长的方法,对基本鱼群算法进行了优化和改进.应用四个典型的测试函数进行仿真实验,分析算法的寻优精度、收敛速度及稳定性.实验结果表明改进后的算法能够较快地收敛至全局较优解,并具有较好的寻优性能.
為瞭剋服基本人工魚群算法收斂速度慢、求解精度不高和易陷入跼部最優的不足,提齣瞭自適應調整人工魚群算法參數的方法,該方法採用箇體魚適應值與整箇魚群的平均適應值作比較,將整箇魚群分為三組,再採用自適應調整每組魚群的視野範圍和步長的方法,對基本魚群算法進行瞭優化和改進.應用四箇典型的測試函數進行倣真實驗,分析算法的尋優精度、收斂速度及穩定性.實驗結果錶明改進後的算法能夠較快地收斂至全跼較優解,併具有較好的尋優性能.
위료극복기본인공어군산법수렴속도만、구해정도불고화역함입국부최우적불족,제출료자괄응조정인공어군산법삼수적방법,해방법채용개체어괄응치여정개어군적평균괄응치작비교,장정개어군분위삼조,재채용자괄응조정매조어군적시야범위화보장적방법,대기본어군산법진행료우화화개진.응용사개전형적측시함수진행방진실험,분석산법적심우정도、수렴속도급은정성.실험결과표명개진후적산법능구교쾌지수렴지전국교우해,병구유교호적심우성능.
In order to overcome the limitations lying in slow convergence, poor accuracy and the propensity of getting into a lo-cal best answer in Artificial Fish-Swarm Algorithm(AFSA), improved measures, which adaptively tuning algorithm parameter of artificial fish-swarm, are presented. This measure accords the comparison between the adaptive value of individual fish and the average adaptive value of the fish-swarm, dividing the whole fish into three groups which including better fish, general fish and poor fish, adaptively turning the step length and view field of fish in each group, in order to optimize and improve the basic algorithm. It analyzes the adapting fish-swarm step length and view field, optimization accuracy, convergence speed and stability of algorithm through four typical test function simulation. It can get the conclusion that adapting fish-swarm’s field of view and steps can make the algorithm converge quickly to the global better solution, and has good optimization performance.