The product price forecasting model based on function-driven was presented by use of LS-SVM.
以最小二乘支持向量机为工具，构建了基于功能驱动的产品价格预测模型。
As the example of the single vegetable species cabbage, its price problem is studied quantificationally in the facts of identification, diagnose, mimic and forecasting by using ARIMA model.
从研究单一蔬菜品种卷心菜开始，利用ARIMA理论和方法，从模型的识别、诊断、拟合与预测定量地研究其价格的问题。
This paper puts forward a model of discovering and forecasting price trend in market, based on neural networks BP algorithms.
提出了一种利用神经网络BP算法模型于发现和预测商业市场价格变化趋势的模型。
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