摘要
小麦叶面积指数是评价其长势和预测产量的重要农学参数,为了提高小麦叶面积指数的估算精度,本文提出了一种基于案例推理的小麦叶面积指数估算方法。利用小麦的10种植被指数,首先建立小麦叶面积指数的统计回归估算模型;然后使用基于案例推理的方法对小麦叶面积指数进行估算。实验结果表明,基于案例推理的方法相对于统计回归模型,提高了小麦叶面积指数的估算精度。说明基于案例推理的小麦叶面积指数估算方法是一种有效可行的方法。
Leaf Area Index （LAI） is one of the important parameters for evaluating wheat growth status and forecasting its yield, in order to enhance the estimation precision of wheat LAI, an estimation method based on case-based reasoning is proposed in this paper. Statistical regression models are constructed for estimating wheat LAI with 10 vegetation indices Firstly, then using the method based on case-based reasoning to estimate wheat LAI. The experimental results show that the case-based reasoning method can enhance the accuracy of wheat LAI estimation compared with statistical regression models. It is concluded that the method based on case-based reasoning is an effective and feasible way for wheat LAI estimation.
出处
《科学技术与工程》
北大核心
2014年第28期58-63,共6页
Science Technology and Engineering
关键词
叶面积指数
估算
基于案例推理
遗传算法
leafarea Index
estimation
case-based reasoning
genetic algorithm
