Knowledge Acquisition Model for Stability Situation Judgement Used in Crowd Evacuation

R. Zhao, Yan Wang, Qiong Liu, Daheng Dong, Cuiling Li
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引用次数: 1

Abstract

In recent years, people’s demand for data analysis and knowledge acquisition from big data is becoming more urgent. Large-scale crowd evacuation also requires a wealth of decision-making knowledge to provide emergency solution guidance. This paper corresponds the crowd size to the granularity of knowledge objects, and proposes a variablegrained knowledge acquisition model for the evolution mechanism of crowd evacuation stability. The rough set matrix calculation model is used to generate the meta-rules. Through the rigorous discretization of the reversible process analysis logic, the meta-rules are automatically simplified into generalized rules with evacuation guiding significance. The explicit knowledge of stability situation in crowd evacuation is discovered. This study provides a scientific decision-making method for timely and accuratejudgment of the crowd stability, rational organization and guidance of safe evacuation, and also provides scientific basis for the prevention of malignant crowding and trampling events with important theoretical and social significance.
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人群疏散中稳定态势判断的知识获取模型
近年来,人们对数据分析和从大数据中获取知识的需求越来越迫切。大规模人群疏散也需要丰富的决策知识来提供应急解决指导。本文将人群规模与知识对象的粒度相对应,提出了一种变粒度的知识获取模型来研究人群疏散稳定性的演化机制。采用粗糙集矩阵计算模型生成元规则。通过对可逆过程分析逻辑的严格离散化,将元规则自动简化为具有疏散指导意义的广义规则。发现了人群疏散过程中稳定状态的显式知识。本研究为及时准确判断人群稳定性、合理组织和指导安全疏散提供了科学的决策方法,也为预防恶性拥挤踩踏事件提供了科学依据,具有重要的理论和社会意义。
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