论文部分内容阅读
公路网规模是区域公路网规划中重要的研究内容和控制性指标。在系统分析影响公路网合理规模的相关因素及约束条件的基础上,对现有预测方法的优缺点进行探讨。考虑经济社会发展对公路网建设的需求特点,提出基于BP神经网络与马尔可夫链的公路网规模组合预测模型,并以中部地区某省为例,对其2020年公路网发展规模进行预测,同时对模型方法的科学性、合理性进行验证。
The scale of highway network is an important research content and a control index in the planning of regional highway network. On the basis of systematically analyzing the relevant factors and constraints that affect the reasonable scale of highway network, the advantages and disadvantages of the existing forecasting methods are discussed. Considering the characteristics of the demand for the construction of highway network from economic and social development, this paper proposes a combined forecasting model of highway network based on BP neural network and Markov chain. Taking a province in the central region as an example, the paper predicts the development scale of highway network in 2020, At the same time, it verifies the scientificity and rationality of the model method.