基于MSE准则的TSK模糊系统的蔬菜价格预测

Vegetable Prices Forecasting based on Mse Criteria TSK Fuzzy System

蔬菜价格波动性大、季节性强,受供求关系、季节、气候等多种因素的影响,蔬菜价格具有高度的非线性、高噪声的属性加大了预测的难度。因此运用基于传统的MSE准则函数应用于蔬菜价格预测的建模,以样本的实际输出和神经网络的预测输出的平方差为误差准则函数,来进行人工神经网络参数学习,通过MSE准则的TSK模糊系统模型来预测蔬菜的价格,最后通过实例验证此方法科学有效。

Vegetable price fluctuates greatly and seasonally. It is influenced by the supply and demand relationship,season, and climate. Vegetable price is difficult to forecast for its high degree of non-linear and high-noise properties. For this reason, the paper applies the traditional MSE guidelines function to vegetable price forecast modeling, makes artificial neural network parameters studying by the Squared-Error of the actual output and the neural network forecast output, forecast vegetable price based on the Mse guidelines TSK fuzzy system, and finally proves that the method is efficient by way of example