系统仿真学报 ›› 2018, Vol. 30 ›› Issue (3): 824-831.doi: 10.16182/j.issn1004731x.joss.201803007

• 仿真建模理论与方法 • 上一篇    下一篇

基于多智能体算法的CA林火空间扩散模型

周国雄, 吴淇, 陈爱斌*   

  1. 中南林业科技大学 计算机与信息工程学院,湖南 长沙 410004
  • 收稿日期:2016-03-09 出版日期:2018-03-08 发布日期:2019-01-02
  • 作者简介:周国雄(1980-),男,湖南嘉禾,博士后,副教授,研究方向为智能控制、无损检测;吴淇(1990-),男,福建三明,本科生,研究方向为智能控制;陈爱斌(通信作者1971-),男,博士,教授,研究方向为图像处理、模式识别、智能系统和林业信息工程。
  • 基金资助:
    国家948项目(2014-4-09),国家自然科学基金(31470659)

Forestry Fire Spatial Diffusion Model Based on Multi-Agent Algorithm with Cellular Automata

Zhou Guoxiong, Wu Qi, Chen Aibin*   

  1. School of Computer and Information Engineering, Central South University of Forestry & Technology, Changsha 410004, China
  • Received:2016-03-09 Online:2018-03-08 Published:2019-01-02

摘要: 针对林火蔓延多相和多组分的性质,提出一种基于多智能体算法的CA林火空间扩散模型。采用基于王正非的CA模型对林火蔓延趋势进行近似模拟。在CA确定的元胞状态转换规则的基础上,结合多智能体算法的自学习及变异的方法,使得实测林火格局与CA规则驱动的演进模式最为接近,实现自动优化CA规则,使得CA蔓延模型的精度提高。通过仿真结果,对比分析传统的Rothermel模型与本文提出的方法,可知在火场面积和火场周长方面,实际林火蔓延过程与本文提出的林火空间扩散模型的实验仿真结果具有较高的相似性。

关键词: 进化智能体, 多智能体算法, 元胞自动机, 规则函数, 林火蔓延

Abstract: In view that forestry fire has the nature of multi-phase and multi-component, a forestry fire spatial diffusion model based on multi-agent algorithm with cellular automata is proposed. A method based on Wang Zhengfei-CA model is employed to approximately simulate the spread of forestry fire. On the basis of the status transition rule determined by CA and using the self-learning and variation methods of multi-agent algorithm, the measured forestry fire pattern is most similar to CA rule-driven evolution model and the CA rule can be automatically optimized. By comparatively analyzing the simulation results of the traditional Rothermel model and the method proposed in this paper, it is found that in the respects of fire area and fire perimeter, the actual forestry fire spread process has higher similarity to the simulation results of the proposed forestry fire spatial diffusion model.

Key words: evolutionary agent, multi-agent algorithm cellular, automata, rules function, forestry fire

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