摘要
航材保障中存在着部分航材因为消耗数据样本小变化大难以进行有效航材消耗预测的问题。支持向量机对小样本数据有很好的适应能力。该模型常用于解决小样本非线性回归问题但参数优化影响着预测结果合理性。人工免疫算法具有较好的数据优化能力,采用人工免疫算法对基于支持向量机航材预测模型参数进行优化有效解决参数取值问题。通过实例证明采用人工免疫算法优化支持向量机模型参数能够为航材预测提供合理有效的预测值。
In the aviation material guarantee,some aviation materials are difficult to predict effectively because of small changes in the consumption data samples.Support vector machines have good adaptability to small sample data.The model is often used to solve nonlinear regression problems with small samples,but parameter optimization affects the rationality of the prediction results.The artificial immune algorithm has good data optimization ability.The artificial immune algorithm is used to optimize the pa⁃rameters of aircraft material prediction model based on support vector machine.An example shows that the optimization of support vector machine model parameters by artificial immune algorithm can provide reasonable and effective predictive values for aircraft material prediction.
作者
杨宜霖
刘臣宇
薛永亮
马中原
孙伟奇
YANG Yilin;LIU Chenyu;XUE Yongliang;MA Zhongyuan;SUN Weiqi(Qingdao Campus of Naval Aviation University,Qingdao 266041;Naval Aviation University,Yantai 264001)
出处
《舰船电子工程》
2020年第5期134-137,共4页
Ship Electronic Engineering
关键词
航材预测
支持向量机
人工免疫
参数优化
aviation material forecast
support vector machine
artificial immunity
parameter optimization
