摘要
反向灰色模型在具有单调递减趋势的时间序列预测中取得了较好的效果,但是初始值较为陈旧,影响了模型的精度。利用遗传算法对x(1)(n)序列初始值进行全局搜索,确定最优初始值,对反向灰色模型进行了优化。并利用高层建筑实际沉降观测数据对该方法进行了验证。结果表明,该优化灰色模型提高了原模型的预测精度,具有较高的实用价值。
Reverse Gray made in time series forecasting model has a monotonically decreasing trend of good results, but initial value quite outdated, affecting the accuracy of the model. In this paper, the genetic algorithm x （n） sequence initial value global search to determine the optimal initial value of the reverse gray model is optimized. And the actual use of high-rise building settlement observation data, the method is validated. The results show that the optimum gray model to improve the prediction accuracy of the original model, with high practical value.
出处
《北京测绘》
2015年第6期88-90,共3页
Beijing Surveying and Mapping
关键词
反向灰色模型
遗传算法
沉降监测
reverse gray model
genetic algorithm
subsidence monitoring
作者简介
路家松（1971-），男，汉族，吉林四平人，本科，主要从事生产测绘工作。
