基于优化GM(1,1)预测模型的产油量预测

To forecast the oil production based on an optimized GM(1,1) forecasting model

本文针对传统GM(1,1)预测模型在初始条件选取上的局限性,应用以x(1)的第n个分量作为初始条件的改进GM(1,1)模型对产油量进行了预测,但并未取得好的预测效果。后本文按照使原始数据序列的x(1)序列与其模拟序列x(∧1)之差的平方和最小的原则,来确定白化权函数中的常数C,构建了优化GM(1,1)模型,在产油量预测中提高了预测精度。

This paper applies the improved GM（1,1） model that regards the n-th vector as its initialization to forecast oil production,but we can＇t get better forecasting effect. Later ,this paper ascertains the constant c in the whitenization weight function and establish the optimized GM（1,1） model according to the principle of making the sum of the squares of the difference between the accumulated sequences of the original sequences and the simulating accumulated sequences least. As a result , we get improvement in forecasting precision.