基于遗传多目标优化的河流自动选取模型

Automated Elimination of River Based on Multi-Objective Optimization Using Genetic Algorithm

在分析河系自身特点以及河流选取基本原则基础上,建立了基于遗传多目标优化的河流自动选取模型:首先建立面向河系空间知识的结构化河流数据模型,然后运用遗传多目标优化算法对河流进行自动选取.该模型综合考虑了河流选取中的河流长度、河流间隔、河流的重要性等指标,同时兼顾了河流选取对河网总体结构特征的保持.实验证明了该思想的合理性和有效性,与传统方法相比,该方法具有较高的自动化和智能化水平.

Based on the structure characteristic of river network and the principle of river selection, a new automated elimination model was established using genetic multi-object optimization algorithm. The structuring river data model facing the river system＇ s spatial knowledge was built firstly, and then the river was auto-selected using genetic multi-object optimization algorithm. The indicators including length, interval and importance of river etc. and the collectivity structure characteristic of river network were taken into account when selecting the river. The results show that the method is reasonable and valid, and more roboticized and intelligent comparing with the traditional method.