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近年来,空中交通复杂性的研究蓬勃发展,如何选取指标分析复杂性成为一个关键技术.本文在对以往复杂性研究进行简单回顾的基础上,明确了指标选取对于复杂性研究的重要意义.结合已有成果,选取定义明确、可定量分析的指标构建了复杂性指标体系.针对指标体系维数多、信息量大等特点,选取灰色关联聚类方法挖掘指标数值的分布规律,实现对指标的提取精炼,从而在运用指标体系分析空中交通复杂性时,既能全面描述问题,又能降低指标维度.根据广州地区16扇区雷达数据,对一类指标进行了计算和聚类分析,验证了该方法的准确性.
In recent years, the research on the complexity of air traffic has been flourishing, and how to select the complexity of index analysis becomes a key technology.Based on a brief review of previous studies on complexity, this paper clarifies the importance of selecting indicators for complexity research. Has been successful, select the definition of a clear, quantitative analysis of indicators to build a complex index system.According to the index system has many features such as large number of information and large amount of information, select the gray relational clustering method to tap the distribution of the index value to achieve the index Extraction and refining, so that when using the index system to analyze the complexity of air traffic, it not only can describe the problem in a comprehensive way, but also can reduce the dimension of index.According to the data of 16 sectors in Guangzhou, a class of indexes are calculated and clustered to verify The accuracy of the method.