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针对粮食最低收购价政策问题,首先采集相关数据并进行预处理(数值化、归一化和缺失值处理),然后分别基于最低收购价等对粮食种植面积的影响问题、执行效果评价问题、规律性问题和合理定价问题建立相应模型,依次采用迭代算法、遗传算法和动态BP神经网络算法对模型求解,最终利用SPSS、STATA统计检验和MATLAB软件编程实现算法,解决粮食最低收购价政策的分析、评价、预测及优化等相关问题.
According to the policy of minimum purchase price of grain, the related data are firstly collected and pre-processed (numericalization, normalization and missing value processing), and then based on the influence of the minimum purchase price on grain acreage, the evaluation of implementation effect, the law Sexual problems and reasonable pricing problems, the model is solved by iterative algorithm, genetic algorithm and dynamic BP neural network algorithm in turn, and finally the SPSS, STATA statistical test and MATLAB software are used to realize the algorithm to solve the policy of minimum purchase price of grain, Evaluation, prediction and optimization and other related issues.