基于神经网络的水产品价格预测模型研究

Research on Prediction Model of Aquatic Production Price Based on Artificial Neural Network

以水产品中鲫鱼为例,选择时间、地理环境和经济条件因素作为输入层变量,价格作为输出单元,输入样本进行训练和仿真,对训练好的网络输入预测样本,将预测结果与市场实际价格进行比较,其相对误差均小于1%。结果证明,所构建的水产品价格预测模型具有良好的精确性和准确性,将神经网络应用于水产品价格预测是可行的。

In this study,crucian carp was selected as a predict species,by using time,geographic factors,environmental and economic conditions as variables at input layer,the price as the output,model training and simulation with the input of samples were carried out.The results showed the relative error was less than 1% between the prices of actual market and the values predicted by the trained network.The results showed the good accuracy and precision of the prediction model of aquatic production established in our study,verified the feasibility of the application of the neural network in the price forecast of aquatic products.