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人工神经网络产量定量评价模型在县域耕地地力评价中的应用
引用本文:孔维娜,李跃进,李双异,裴久渤,汪景宽. 人工神经网络产量定量评价模型在县域耕地地力评价中的应用[J]. 国土与自然资源研究, 2012, 0(2): 30-32
作者姓名:孔维娜  李跃进  李双异  裴久渤  汪景宽
作者单位:内蒙古农业大学生态环境学院;沈阳农业大学土地与环境学院
基金项目:农业部耕地地力调查与评价项目;国家自然科学基金项目(40871142)
摘    要:以辽宁省彰武县为研究对象,在AHP-模糊评价方法的基础上尝试建立耕地地力的ANN-产量定量评价模型。与传统方法相比,模型不需要确定权重,并且能够反映耕地地力评价的非线性特征,消除了传统方法确定权重时人为因素的影响,增加了评价结果的客观性。通过与传统方法的对比发现,得到了较为一致的评价结果,为耕地地力的定量评价探索了一条新的道路。

关 键 词:耕地地力  人工神经网络  定量评价模型

Application for Cultivated Land Fertility Evaluation in County Level Based on ANN-Productivity Quantitative Evaluation Model
Affiliation:KONG Wei-na et al(College of Ecology and Environmental Sciences,Inner Mongolia Agricultural University,China)
Abstract:Take the Liaoning Province Zhangwu County as the object of study,on the basis of AHP-fuzzy evaluation method,the ANN-productivity quantitative evaluation model was attempted to establish.Compared with the traditional method,the model does not need to determine the weight,and can reflect the non-linear characteristic of the cultivated land fertility evaluation,The influence of artificial factors in the traditional method of determining the weights can be eliminated,also the objectivity of evaluation results can be increased.Then the evaluation results were compared with that from conventional method for getting relatively consistent evaluation results,and this method has explored a new way for the cultivated land fertility quantitative evaluation.
Keywords:cultivated land fertility  ANN-productivity  quantitative evaluation model
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