Windblown sand control decision-making support system based on parallel intelligence: Taklimakan desert highway and its sand-breaking system

Fangle CHANG; Mengzhen KANG; Xiujuan WANG; Jiaqiang LEI; Fei-Yue WANG

doi:10.11959/j.issn.2096-6652.202150

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Windblown sand control decision-making support system based on parallel intelligence: Taklimakan desert highway and its sand-breaking system

Papers and Reports | 更新时间：2024-06-05

- Windblown sand control decision-making support system based on parallel intelligence: Taklimakan desert highway and its sand-breaking system
- Chinese Journal of Intelligent Science and Technology Vol. 3, Issue 4, Pages: 499-506(2021)
- 作者机构：
  
  1. 中国科学院自动化研究所复杂系统管理与控制国家重点实验室，北京100190
  2. 浙江大学宁波研究院，浙江宁波315100
  3. 中国科学院自动化研究所北京智能技术工程研究中心，北京100190
  4. 中国科学院新疆生态与地理研究所，新疆乌鲁木齐 830011
  5. 中国科学院大学人工智能学院，北京 100049
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-6652.202150
  CLC： TP18
- Published Online：2021-12，
  
  Published：15 December 2021
- 稿件说明：
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Fangle CHANG, Mengzhen KANG, Xiujuan WANG, et al. Windblown sand control decision-making support system based on parallel intelligence: Taklimakan desert highway and its sand-breaking system[J]. Chinese journal of intelligent science and technology, 2021, 3(4): 499-506.
DOI：

Fangle CHANG, Mengzhen KANG, Xiujuan WANG, et al. Windblown sand control decision-making support system based on parallel intelligence: Taklimakan desert highway and its sand-breaking system[J]. Chinese journal of intelligent science and technology, 2021, 3(4): 499-506. DOI： 10.11959/j.issn.2096-6652.202150.

摘要

针对风沙防护治理系统难以建模、难以解析预测等问题，以塔克拉玛干沙漠公路及其防沙体系为研究对象，提出平行智能风沙防护治理决策支持系统。基于防沙专家常年积累的经验知识，结合实际系统风沙环境信息，模拟风沙防护治理过程，构建沙漠公路防沙体系人工系统；基于计算实验，评估防沙体系人工系统的防沙效果，通过与实际系统进行比较与学习，对系统进行评估与校准；基于平行智能理论，分析风沙防护治理决策支持系统，实现人工系统与实际系统的相互学习、相互借鉴，为风沙防护治理提供决策支持，促进风沙环境可持续化发展。

Abstract

Using Taklimakan desert highway and its sand-breaking system as the research object for complex system management and control

the ACP-based parallel intelligence theory to deal with the problems of the difficulty in modeling

analyzing

and predicting of sand-breaking system was applied

to realize the intelligent decision support for sand-breaking system management and control

support the sustainable development of aeolian environment.The expert experience knowledge to construct the artificial desert highway sand-breaking system was extracted by simulating physical process.The sand-control efficiency index of the artificial system was calculated using equations

then evaluated and modified by comparing and learning with the actual system.Using parallel intelligent theory

the artificial system and the actual system can learn from each other to provide decision support for sand control.

关键词

Keywords

references

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