【摘要】 通过粗糙集BP神经网络模型的构建,对影响煤炭物流中心选址决策的指标进行约简,提取影响选址评价的主要因素用属性约简算法约简,将降维后的数据送入网络学习和训练,最后用训练好的网络对测试样本进行检验。该模型使学习训练的速度和识别率提高了,为煤炭物流中心选址决策提供了一种更为有效和实用的新方法。更多还原

【Abstract】 To research the location selection research of coal logistics nodes, constructs a BP neural network model based on rough set. Attribute reduction is firstly used to obtain the mainly components of the factors of customer satisfaction evaluation to reduce the number of dimensionalities of the decision talbe. After the dimensionality reduction process, put the new data into BP neural network to train it.Stumilation results show that, compared with the BP neural network nodel, BP neural network model based on rough set gets a higher rate on speed and recognition when trained under the worked data. The results indicate that BP neural network model based on rough set should be a better way to evaluation of the location selection research of coal logistics nodes.更多还原