【作者】 甘明鑫；

【Author】 GAN Ming-xin(School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China)

【机构】 北京理工大学管理与经济学院；

【摘要】 粮食产量预测是农业经济管理中的一个重要环节,本文以小麦产量预测模型为例论述了应用于全国粮食产量预测的神经网络模型建立的关键步骤和指标分析选取的方法,并在模型参数优选的基础上用此方法用历史数据进行了预测分析。预测结果表明,该模型可提高粮食产量预测准确性,有效性,实际的预测结果分析说明了该方法的先进性和可行性。更多还原

【Abstract】 The forecasting of foodstuff output is an important issue in the agricultural economic management. This paper proposes a method of the key modeling process and the factor choosing of the neural network forecasting model for the foodstuff output in China by introducing a forecasting model of the output of wheat. Then we use historical data to forecast the output based on the optimal factors of this model, the analysis of this result shows that using this model can enhance the precision and effectiveness of foodstuff output forecasting. The real forecasting result indicates the advantage and the feasibility of this method.更多还原