基于蚁群聚类的RBF NN海洋环境下武器效能评估

摘要

海洋环境复杂多变，武器装备作战效能影响要素众多并且机理复杂，效能评估问题难度加大。针对海洋环境影响下武器效能的评估问题，将蚁群聚类算法与RBF神经网络相结合，提出了基于蚁群聚类的RBF神经网络武器作战效能评估方法并建立评估模型。通过蚁群聚类算法确定RBF神经网络隐含层神经元的中心值，并且为了得到最优聚类结果，在蚁群聚类中加入了局部搜索。最后，利用样本数据对该模型进行训练，并对特定条件下武器作战效能进行评估，实验证明此评估模型具有一定的可行性和有效性。%Aiming at the operational effectiveness evaluation problem of weapon equipment under marine environment,ant colony clustering algorithm is combined with RBF neural network, an operational effectiveness evaluation method of weapon equip-ment under marine environment is proposed based on ant colony clustering and RBF neural network and its corresponding model is established in this paper.Ant colony clustering algorithm is used to get the centers of hidden layer neurons of RBF neural network,and local search is added to ant colony clustering algorithm to find the best clustering result.