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Research on the Traffic Flux Forecast Based on Fuzzy Linear Regression Model

机译:基于模糊线性回归模型的交通通量预测研究

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In this paper, the flux forecast model is studied which based on fuzzy linear regression, and the equation parameters of it are determined by fitting degree and ambiguity degree. They are verified by true data of Jinshan Road on Jiangdong strict in Hengyang City. The fitting degree are almost above 0.5, and fitting the average relative deviation is 6.00%.Compared to the general results of the multiple linear regression, the results of fuzzy linear regression forecast flow projections, are more effective than the latter, with better practicality and higher promotion of value.
机译:在本文中,研究了基于模糊线性回归的磁通预测模型,并通过拟合度和模糊度来确定其等式参数。他们是由横阳市严格严格的金山路的真实数据验证。拟合度几乎高于0.5,拟合平均相对偏差为6.00%。与多元线性回归的一般结果相比,模糊线性回归预测流程的结果比后者更有效,具有更好的实用性和升级价值较高。

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