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Forecast Model of Vehicle Effectiveness Based on Factors Analysis and RBF Neural Networks

机译:基于因子分析和RBF神经网络的车辆效能预测模型

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摘要

Effectiveness forecast of especial vehicle is important in vehicle development and compare research. This paper establishes forecast model of vehicle effectiveness by factors analysis with interpretability, and RBF (radial basis function) neural networks with short training time and precise function. Secondly, the result of forecasted and original is contrasted together, then the quality and creditability of forecast model can be verified.
机译:特殊车辆的有效性预测在车辆发展和比较研究方面都很重要。本文通过训练时间和精确函数的解释性和RBF(径向基函数)神经网络来建立载体效能的预测模型。其次,预测和原始结果的结果形成在一起,然后可以验证预测模型的质量和可信度。

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