Study on Evaluation Model of Emergency Rescue Capability of Chemical Accidents Based on PCA-BP.

Jianghong Liu,Junfeng Wu,Weisi Liu,Ricardo Aler

doi:10.1155/2021/8869608

Jianghong Liu, Junfeng Wu + Show 2 more

Open Access

https://doi.org/10.1155/2021/8869608

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Abstract

The emergency management of chemical accidents plays an important role in preventing the expansion of chemical accidents. In recent years, the evaluation and research of emergency management of chemical accidents has attracted the attention of many scholars. However, as an important part of emergency management, the professional rescue team of chemicals has few evaluation models for their capabilities. In this study, an emergency rescue capability assessment model based on the PCA-BP neural network is proposed. Firstly, the construction status of 11 emergency rescue teams for chemical accidents in Shanghai is analyzed, and an index system for evaluating the capabilities of emergency rescue teams for chemicals is established. Secondly, the principal component analysis (PCA) is used to perform dimension reduction and indicators' weight acquisition on the original index system to achieve an effective evaluation of the capabilities of 11 rescue teams. Finally, the indicators after dimensionality reduction are used as the input neurons of the backpropagation (BP) neural network, the characteristic data of eight rescue teams are used as the training set, and the comprehensive scores of three rescue teams are used for verifying the generalization ability of the evaluation model. The result shows that the proposed evaluation model based on the PCA-BP neural network can effectively evaluate the rescue capability of the emergency rescue teams for chemical accidents and provide a new idea for emergency rescue capability assessment.

Highlights

Due to the properties of hazardous chemicals, such as toxicity, corrosiveness, explosiveness, flammability, and combustion support, there are huge risks in their production, transportation, storage, sales, use, and disposal
Wang et al [2] proposed a disaster management control capability assessment model based on the Capability Maturity Model (CMM). is model evaluates the capability of the organization from eight aspects and divides the capability assessment results into four levels, which provides general assessment guidelines for different types of emergency management organizations
Lin [3] analyzed the nature of emergency rescue capabilities from the perspective of the entire city and established an urban emergency rescue capability evaluation system based on Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE)

Summary

Introduction

Due to the properties of hazardous chemicals, such as toxicity, corrosiveness, explosiveness, flammability, and combustion support, there are huge risks in their production, transportation, storage, sales, use, and disposal. Zhu et al [6] used Bayesian networks to propose a framework for dynamically evaluating explosion accidents in chemical plants to support prevention, management, and real-time warning He et al [7] established a Petri net model of emergency process of chemical accidents in order to evaluate the emergency capability, which can dynamically evaluate the emergency capability of chemical accidents. In order to reasonably evaluate the capabilities of professional emergency rescue teams for hazardous chemical accidents, this study surveyed 11 professional rescue teams in Shanghai, analyzed the status of these teams, constructed a rescue capacity assessment index system, and built a rescue capability evaluation model combined with BP neural network. E trained BP neural network evaluation model can well evaluate the capabilities of professional emergency rescue teams for hazardous chemical accidents, providing a new idea for emergency rescue capability assessment E dimensionality-reduced feature factors were used as the input units of the BP neural network. is method can reduce the influence of human factors in the evaluation process and simplify the structure of the artificial neural network and reduce the computational complexity of the evaluation model. e trained BP neural network evaluation model can well evaluate the capabilities of professional emergency rescue teams for hazardous chemical accidents, providing a new idea for emergency rescue capability assessment

Methods

Data Processing

Implementation of BP Neural Network

Evaluation index

Simulation and Result Analysis of BP Neural Network Evaluation Model

Conclusion