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Load Forecasting of Coal-Fired Unit Based on SVM Model

机译:基于SVM模型的燃煤单位负荷预测

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In order to obtain accurate load forecasting of coal-fired unit, a new algorithm based on Support Vector Machine (SVM) method is presented. This algorithm establishes a model to reflect the complicated relation between the load of coal-fired unit and the furnace flame Images. The trained SVM model is applied to a 660MW coal-fired unit to forecast the load with two groups of test samples. The results are compared with that of BP neural network model. It is shown the SVM model is more accurate than the BP NN model. The SVM method can satisfy the demand of engineering applications with the advantages of high forecasting accuracy and more generalized performance.
机译:为了获得准确的负载预测燃煤单元,提出了一种基于支持向量机(SVM)方法的新算法。该算法建立了一种模型,以反映燃煤单元的负载与炉火图像之间的复杂关系。培训的SVM模型应用于660MW燃煤单元,以预测具有两组测试样品的负载。结果与BP神经网络模型进行了比较。显示SVM模型比BP NN模型更准确。 SVM方法可以满足工程应用的需求,具有高预测精度和更广泛性的性能的优点。

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