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土壤养分肥力等级是土壤特性的综合反映,也是揭示土壤条件动态的最敏感的指标。对它的评价涉及多个指标,很难用常规方法进行。人工神经网络由于有大规模并行处理、分布式存储、自适应性、容错性等特点,可以解决复杂的非线性高维同题,本研究拟采用建立的土壤养分肥力等级BP神经网络评价模型,对山西省大同地区的土壤养分肥力等级进行评价。
Soil nutrient fertility level is a comprehensive reflection of soil characteristics, but also to reveal the dynamics of soil conditions the most sensitive indicator. Evaluation of it involves multiple indicators, it is difficult to use the conventional method. Due to its large-scale parallel processing, distributed storage, self-adaptability and fault tolerance, artificial neural network can solve complex nonlinear high dimensional problems. In this study, the proposed evaluation model of soil nutrient fertility level BP neural network was proposed, Soil fertility level in Datong of Shanxi Province was evaluated.