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。
By means of introducing ripe geometrical Brown movement model for common commodity price forecasting a coal price fluctuation model of coal market is established.
通过引入用于预测普通商品价格的较成熟的几何布朗运动模型建立了燃煤市场的煤价波动模型。
Comparing to the results from traditional support vector machine for forecasting market clearing price and price spike in power market, the TGA-SVM manifests the more accurate forecasting results.
将其应用于电力市场出清价及价格钉的预测实例研究，与传统的支持向量机预测结果比较，三角旋回支持向量机具有更高的预测精度。
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