火力与指挥控制
火力與指揮控製
화력여지휘공제
FIRE CONTROL & COMMAND CONTROL
2014年
12期
58-61
,共4页
粒子群优化算法(PSO)%聚焦距离变化率%自适应惯性权重%速度最大值线性递减%粒子替换
粒子群優化算法(PSO)%聚焦距離變化率%自適應慣性權重%速度最大值線性遞減%粒子替換
입자군우화산법(PSO)%취초거리변화솔%자괄응관성권중%속도최대치선성체감%입자체환
particle swarm optimization%focus distance changing rate%self-adaptive inertia weight%maximum speed linear regression%particle replacement
在建立多种类型武器目标分配模型的基础上，提出了一种求解该模型的改进粒子群算法。首先，定义粒子聚焦距离变化率，使惯性权重依据聚焦距离变化率自适应调整；其次，采用速度最大值线性递减的策略平衡算法收敛精度与全局寻优能力之间的矛盾；最后，粒子替换策略使算法改善了因自适应惯性权重的引入而造成收敛速度变慢的问题。仿真结果表明，提出模型和算法合理有效，算法收敛快，适合求解各种种群规模的武器目标分配问题。
在建立多種類型武器目標分配模型的基礎上，提齣瞭一種求解該模型的改進粒子群算法。首先，定義粒子聚焦距離變化率，使慣性權重依據聚焦距離變化率自適應調整；其次，採用速度最大值線性遞減的策略平衡算法收斂精度與全跼尋優能力之間的矛盾；最後，粒子替換策略使算法改善瞭因自適應慣性權重的引入而造成收斂速度變慢的問題。倣真結果錶明，提齣模型和算法閤理有效，算法收斂快，適閤求解各種種群規模的武器目標分配問題。
재건립다충류형무기목표분배모형적기출상，제출료일충구해해모형적개진입자군산법。수선，정의입자취초거리변화솔，사관성권중의거취초거리변화솔자괄응조정；기차，채용속도최대치선성체감적책략평형산법수렴정도여전국심우능력지간적모순；최후，입자체환책략사산법개선료인자괄응관성권중적인입이조성수렴속도변만적문제。방진결과표명，제출모형화산법합리유효，산법수렴쾌，괄합구해각충충군규모적무기목표분배문제。
On the basis of establishing various types of weapon target assignment models,an improved particle swarm algorithm is proposed to solve the model. First of all,inertia weight is becoming adaptive expressed as functions of focus distance changing rate by defining them.Second,the strategy balancing algorithm of maximum speed linear regression is adopted to balance the contradiction between convergence accuracy and the global optimization ability; Finally,particle replacement strategy improves the algorithm the slow convergence speed problem caused by the introduction of self-adaptive inertia weight. Simulation results show that the proposed model and algorithm are reasonable and effective with fast converges,which are suitable for solving weapon target assignment problem of all kinds of population size.
