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首页> 外文会议>2011 6th International Conference on Product Innovation Management >Research on vessel price interval forecasting model based on the rough insensitive loss function SVR
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Research on vessel price interval forecasting model based on the rough insensitive loss function SVR

机译：基于粗糙不敏感损失函数SVR的船舶价格区间预测模型研究

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Because the continually fluctuant price of vessel, the forecast of interval price is more dependable than precise data. A arithmetic of the rough ε-insensitive loss function-based support vector machines is introduced, which is able to forecast the interval value. In order to improve the precision of forecast, parameters of the arithmetic is optimized by chaos traverse. On the way, fore-learning objective function is established, to replace the minimum training error object function which easily leads to over training. According to above, the forecasting model of the vessel interval price is founded. Experimental results show that this RSVR model can forecast the vessel interval price has a high precision, and the fore-learning objective can reduce the over-training problems.
机译：由于船舶价格的不断波动，区间价格的预测比精确数据更可靠。介绍了一种基于ε-不敏感损失函数的支持向量机的算法，该算法能够预测区间值。为了提高预测的精度，通过混沌遍历对算法的参数进行了优化。在此过程中，建立了预学习目标函数，以取代最小训练误差目标函数，该函数容易导致过度训练。综上所述，建立了船舶区间价格的预测模型。实验结果表明，该RSVR模型可以预测船舶区间价格具有较高的精度，并且以学习为目标可以减少训练过度的问题。

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