| 大规模高维数据集环境下的路面使用性能评价方法研究 |
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| 引用本文： | 何琼,叶茎,陈铁.大规模高维数据集环境下的路面使用性能评价方法研究[J].自动化技术与应用,2011,30(9):1-5. |
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| 作者姓名： | 何琼 叶茎 陈铁 |
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| 作者单位： | 武汉软件工程职业学院,湖北 武汉,430205 |
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| 基金项目： | 湖北省高教科研项目(编号2009361) |
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| 摘 要： | 传统中由单一的神经网络等算法所构架起的评价模型主要存在着精度低、网络学习速度慢等不合理之处.为此,提出了基于粗糙集和RBF神经网络的大规模数据集环境下的评价方法.首先详解了粗糙集理论对大规模高维数据所确定的宽泛属性集的分类、约简；然后把处理后的数据指标作为RBF神经网络的输入进行训练、仿真.以高速公路路面性能使用评价为...
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| 关 键 词： | 粗糙集 RBF神经网络 大规模高维数据集 路面使用性能 评价模型 |
Research on Pavement Performance Evaluation with Large High-dimensional Data Sets |
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| HE Qiong,YE Jing,CHEN Tie.Research on Pavement Performance Evaluation with Large High-dimensional Data Sets[J].Techniques of Automation and Applications,2011,30(9):1-5. |
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| Authors: | HE Qiong YE Jing CHEN Tie |
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| Affiliation: | HE Qiong,YE Jing,CHEN Tie(Wuhan Vocational college of Software and engineering,Wuhan 430205 China) |
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| Abstract: | The evaluation model is constructed by single neural network has many faults with the large high-dimensional data sets,such as low accuracy,slow speed and so on.Therefore,a new evaluation way based on rough set & RBF neural network with the large high-dimensional data sets is proposed.Firstly,it uses rough set in classing and simplifying the broad attribute sets which is determined by large high-dimensional data sets;Then it establishes the RBF neural network model to deal with the index which is simplified... |
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| Keywords: | rough set RBF neural network large high-dimensional data sets pavement performance evaluation model |
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