摘要
长期以来,建设用地趋势预测均采用静态思想,即假设影响建设用地变化的内外作用力不变,通过统计学模型进行外推。在面对新数据加入时,这种预测思想没有充分利用原预测结果和新数据的关系,需要对模型重新进行解算。针对这一问题,提出了一种在新数据加入的情况下,基于原有预测结果,采用一元线性回归思想,利用最小二乘原理对预测值进行动态修正的预测方法。研究表明,经该方法修正后的结果能够替代重新预测得到的结果。
The traditional methods for construction land forecasting are based on static data which simulate construction based on the trend extension method. However, when new data are acquired, these methods can not consider the relationship between new data and the original prediction results, and thus, construction land area needs to be reforecasted. This paper proposes a model which uses one-variable linear regression and least square method to correct prediction results dynamically when a type of new data is acquired. The results show that the corrected result is able to fit and replace the predictive values which are reprocessed using the new data.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2014年第1期95-99,105,共6页
Geomatics and Information Science of Wuhan University
基金
国家科技支撑计划资助项目(2012BAH24B00)~~
关键词
建设用地
预测
动态修正
最小二乘原理
construction land
forecast
dynamic correction
least square method
