Scenario construction and deduction for railway emergency response decision-making based on network models

Shi, Lingyuan; Yang, Xin; Li, Jue; Wu, Jianjun; Sun, Huijun

doi:10.1016/j.ins.2021.12.071

Cited by 16 publications

(4 citation statements)

References 32 publications

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“…The process of scenario response could be divided into scenario concept, scenario description and element extraction, scenario evolution, scenario network construction, and scenario projection [ 12 ]. Due to the dynamic and unpredictability of emergencies, how to use existing situations to infer the development of future emergencies trend is the focus at present.…”

Section: Methodsmentioning

confidence: 99%

“…Scenario construction can help decision-makers find the set of events and elements that cause the target scenario system to move from the current state to future development and, thus, provide contingency plans to hinder an undesirable evolution. At present, scenario building is widely used in scenic spots, railroads, cities, mines, and other scenarios, aiming to summarize and extract key elements of various emergencies in different scenarios and then carry out emergency capability assessment, scenario evolution analysis, and association rule mining, with response strategies and accident evolution probability calculation in the respective application scope [ 10 , 11 , 12 , 13 ]. In addition, in the field of material leakage and diffusion research, including marine oil spills and chemical tank leaks, scenario-based construction provides a strong basis for managers to develop prevention and control plans, implement emergency decisions, and analyze the causes of accidents [ 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The Scenario Construction and Evolution Method of Casualties in Liquid Ammonia Leakage Based on Bayesian Network

Zhao

Wang

et al. 2022

IJERPH

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In China, food-freezing plants that use liquid ammonia, which were established in the suburbs in the 1970s, are being surrounded by urban built-up areas as urbanization progresses. These plants lead to extremely serious casualties in the event of a liquid ammonia leakage. The purpose of this thesis was to explore the key factors of personnel protection failure through the scenario evolution analysis of liquid ammonia leakage. The chain of emergencies and their secondary events were used to portray the evolutionary process of a full scenario of casualties caused by liquid ammonia leakage from three dimensions: disaster, disaster-bearing bodies, and emergency management. A Bayesian network model of liquid ammonia leakage casualties based on the scenario chain was constructed, and key nodes in the network were derived by examining the sensitivity of risk factors. Then, this model was applied to a food-freezing plant in Beijing. The results showed that inadequate risk identification capability is a key node in accident prevention; the level of emergency preparedness is closely related to the degree of casualties; the emergency disposal by collaborative onsite and offsite is the key to avoiding mass casualties. A basis for emergency response to the integration of personnel protection is provided.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Scenario Construction and Evolution Method of Casualties in Liquid Ammonia Leakage Based on Bayesian Network

Zhao

Wang

et al. 2022

IJERPH

View full text Add to dashboard Cite

show abstract

“…Adopting a scientific approach is imperative for disaster mitigation. Currently, both domestic and international researchers have conducted extensive research on disaster management, focusing on various technical aspects such as communications, computers and networks, geographic information systems (GIS), global positioning systems (GPS), among others [5][6][7]. Notably, significant contributions have been made in the development of advanced machine learning and optimization algorithms in this field.…”

Section: Introductionmentioning

confidence: 99%

Effectiveness Evaluation of Emergency Rescuing Plans Oriented to Urban Waterlogging Based on a Neural Network Model

Zhang,

Huang,

Geng

et al. 2024

IEEE Access

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In response to the significant impact of urban waterlogging on residents, the economy, and urban infrastructure in recent years, this study introduces an innovative wargame-based evaluation approach for emergency rescue plans. The primary goal of this research is to improve emergency rescue capabilities while minimizing costs and identifying gaps in existing emergency rescue plans. To effectively evaluate these capabilities, we extract specific content related to OODA (Observe, Orient, Decide, Act) dynamics in rescue actions. Furthermore, a comprehensive index system is developed to evaluate emergency rescue capabilities in the context of urban waterlogging scenarios. To address the challenges associated with intelligent optimization and evaluation of such systems, we employ a radial basis function neural network and conduct wargame experiments to obtain data and measure capability indices. The evaluation model is trained using data samples to ensure robust performance. In addition to the proposed model evaluation and analysis framework, we also present an evaluation and analysis method for RBF (Radical Basis Function) neural networks and compare the prediction results with those obtained from GRNN (Generalized Regression Neural Network), PNN (Product-based Neural Network), and BP (Back Propagation) neural network algorithms. This model efficiently processes and fits data by simulating expert experience for evaluation purposes. Such an approach leverages machine learning's sensitivity to data characteristics, effectively avoiding the influence of human factors while stably reflecting the mapping relationship between indicators and performance outcomes. This research presents a novel solution with significant implications for the development of urban emergency rescue systems that address the challenges posed by urban waterlogging incidents.

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“…This method can effectively utilize accumulated experience in the absence of in-depth knowledge. CBR has been widely applied directly or indirectly to solve complex problems, such as in marine emergency rescue [15], urban water supply networks [16], environmental emergency response decisions [17], marine oil spill emergency responses [18], ontological metro accidents [19], fire emergency decisions in high-rise buildings [20], judicial case recommendations [21], railway emergency response decision-making [22], emergency decision-making system for the South-to-North Water Diversion Project [23], forest fire risk forecasting [24] and in other fields. The application of the CBR method in coal mine safety has mainly focused on hidden danger identification and control [25], coal mine disaster early warning [26], coal and gas outburst accident prevention [27], coal mine water disaster [28] and coal mine gas explosion accidents [29]; however, the application of the CBR method in the generation of an emergency response plan for spontaneous combustion has not yet been explored.…”

Section: Introductionmentioning

confidence: 99%

Emergency Response Plan for Spontaneous Combustion Based on Case-Based Reasoning

et al. 2023

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In order to avoid missing the best opportunity for emergency rescue in the event of spontaneous combustion and to prevent accidents from developing further, this paper proposed a method to generate an emergency response plan for spontaneous combustion based on case-based reasoning (CBR). Firstly, we adopted Hadoop big data retrieval technology to establish a case library for spontaneous combustion; then, our team applied CBR technology and introduced the differential determination symbol to calculate case similarity; furthermore, we quickly generated an emergency response plan for spontaneous combustion with the help of the Python program; and finally, we used a case to verify the effectiveness of the method. Overall, the results showed that the emergency response plan generated using this proposed method was consistent with the actual situation of the accident case and, compared with other relevant representative algorithms, the results in this paper were more accurate. In practice, this method may be helpful in providing support for generating emergency response plans for spontaneous combustion.

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Scenario construction and deduction for railway emergency response decision-making based on network models

Cited by 16 publications

References 32 publications

The Scenario Construction and Evolution Method of Casualties in Liquid Ammonia Leakage Based on Bayesian Network

The Scenario Construction and Evolution Method of Casualties in Liquid Ammonia Leakage Based on Bayesian Network

Effectiveness Evaluation of Emergency Rescuing Plans Oriented to Urban Waterlogging Based on a Neural Network Model

Emergency Response Plan for Spontaneous Combustion Based on Case-Based Reasoning

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