摘要
改进的灰色拓扑预测结合了GM(1,1)模型、拓扑预测与最小二乘法.它通过对一些具有波动性的少量数据进行分析得出比较接近实际的预测值,较大程度上减少了误差.本文通过使用该算法,很好地对高考考生填报志愿时要报考学校的下一年分数进行了预测,验证了它的实际运用价值.
Combined with GM(1,1) model,topology prediction and least squares method,the prediction topology was improved.Through analyzing some of the small amount of wavy data,it can get the predictive value which is closer to the actual analysis,and reduce the error in a large degree.This algorithm can well predict the scores of the following year for the candidates when they apply for voluntary reporting,and its application value was verified.
出处
《佳木斯大学学报(自然科学版)》
CAS
2009年第5期748-749,756,共3页
Journal of Jiamusi University:Natural Science Edition
基金
2007年大学生科技创新基金项目
关键词
GM(1
1)模型
最小二乘法
灰色拓扑改进预测算法
考生填报志愿
GM(1
1) model
least square method
improved gray topology prediction algorithm
candidates to declare their voluntary