改进布谷鸟算法优化混合核LSSVM的卷烟销售量预测

摘要

为了提高卷烟销售量预测精度，提出了基于一种改进布谷鸟算法（MCS）优化混合核最小二支持向量机（LSSVM）的卷烟销售量预测模型（MCS-LSSVM）。收集卷烟销售量数据，并构建LSSVM学习样本，然后混合核函数的LSSVM对样本进行训练，并采用改进布谷鸟算法对混合核函数参数进行优化，最后建立卷烟销售量预测模型，并用于某卷烟公司卷烟销售的预测。结果表明，相对于对比模型，ICS-LSSVM模型获得了更优的建模效果和更高的预测精度。%In order improve the forecast accuracy of cigarette sales, this paper proposes a cigarette sales forecasting model based on hybrid kernels Least Square Support Vector Machine(LSSVM)which parameters are optimized by Modified Cuckoo Search(MCS)algorithm. Firstly, the data of cigarette sales are collected to build the LSSVM sample, then the hybrid kernel function LSSVM is used to train samples, and the improved cuckoo algorithm is used to optimize the parameters of hybrid kernel function, finally, cigarette sales forecast model is established and the performance is tested by some ciga-rette sales data. The results show that, compared with other models, the proposed model has good modeling effect and higher forecasting accuracy.