Research on Reconstruction of Emergency Decision-Making System Based on Big Data

Author(s):  
Jun Wang
2012 ◽  
Vol 452-453 ◽  
pp. 937-941
Author(s):  
Rong Yu

In order to provide a high degree of safety, the transport of Nuclear waste material is highly closely regulated. However, the transportation accidents still happened overtime. Considering the high risk and huge disaster effects induced by the transportation accidents of the nuclear waste material, the emeregency management of the nuclear waste materrial transportation needs to be prepared in advance. The author introduced an improved emergency decision making system model, to integreate the relating department working efficiently together in this paper. This paper also briefly points out the emeregency rescue requirements and describes the development and implementation of emeregency management on the nuclear waste materrial transportation accidents.


2021 ◽  
Author(s):  
Guang-Jun Jiang ◽  
Hong-Xia Chen ◽  
Hong-Hua Sun ◽  
Mohammad Yazdi ◽  
Arman Nedjati ◽  
...  

2018 ◽  
Vol 10 (10) ◽  
pp. 3453 ◽  
Author(s):  
Jiyong Ding ◽  
Juefang Cai ◽  
Guangxiang Guo ◽  
Chen Chen

With the rapid development of the urbanization process, rainstorm water-logging events occur more frequently in big cities in China, which causes great impact on urban traffic safety and brings about severe economic losses. Water-logging has become a hot issue of widespread concern in China. As one kind of natural disasters and emergencies, rainstorm water-logging has the uncertainties of occurrence, development, and evolution. Thus, the emergency decision-making in rainstorm water-logging should be carried out in stages according to its development trend, which is very complicated. In this paper, an emergency decision-making method was proposed for urban water-logging with a hybrid use of dynamic network game technology, Bayesian analysis, and multi-attribute utility theory. The dynamic game process between “rainstorm water-logging” and “decision-making group” was established and the dynamic generation of emergency schemes was analyzed based on Bayesian analysis in various stages of water-logging. In terms of decision-making attributes, this paper mainly considered two goals, i.e., ensuring smooth traffic and controlling emergency cost. The multi-attribute utility theory was used to select the final scheme. An example analysis in Guangzhou of China showed that the method is more targeted and can achieve emergency management objectives more effectively when compared with traditional methods. Therefore, it can provide reference for the scientific decision-making of emergency management in urban rainstorm water-logging.


Symmetry ◽  
2017 ◽  
Vol 9 (10) ◽  
pp. 234 ◽  
Author(s):  
Liang Wang ◽  
Álvaro Labella ◽  
Rosa M. Rodríguez ◽  
Ying-Ming Wang ◽  
Luis Martínez

2018 ◽  
Vol 7 (3.1) ◽  
pp. 63 ◽  
Author(s):  
R Revathy ◽  
R Aroul Canessane

Data are vital to help decision making. On the off chance that data have low veracity, choices are not liable to be sound. Internet of Things (IoT) quality rates big data with error, irregularity, deficiency, trickery, and model guess. Improving data veracity is critical to address these difficulties. In this article, we condense the key qualities and difficulties of IoT, which impact data handling and decision making. We audit the scene of estimating and upgrading data veracity and mining indeterminate data streams. Also, we propose five suggestions for future advancement of veracious big IoT data investigation that are identified with the heterogeneous and appropriated nature of IoT data, self-governing basic leadership, setting mindful and area streamlined philosophies, data cleaning and handling procedures for IoT edge gadgets, and protection safeguarding, customized, and secure data administration.  


10.2196/19428 ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. e19428
Author(s):  
Liheng Gong ◽  
Xiao Zhang ◽  
Ling Li

Background During cardiac emergency medical treatment, reducing the incidence of avoidable adverse events, ensuring the safety of patients, and generally improving the quality and efficiency of medical treatment have been important research topics in theoretical and practical circles. Objective This paper examines the robustness of the decision-making reasoning process from the overall perspective of the cardiac emergency medical system. Methods The principle of robustness was introduced into our study on the quality and efficiency of cardiac emergency decision making. We propose the concept of robustness for complex medical decision making by targeting the problem of low reasoning efficiency and accuracy in cardiac emergency decision making. The key bottlenecks such as anti-interference capability, fault tolerance, and redundancy were studied. The rules of knowledge acquisition and transfer in the decision-making process were systematically analyzed to reveal the core role of knowledge reasoning. Results The robustness threshold method was adopted to construct the robustness criteria group of the system, and the fusion and coordination mechanism was realized through information entropy, information gain, and mutual information methods. Conclusions A set of fusion models and robust threshold methods such as the R2CMIFS (treatment mode of fibroblastic sarcoma) model and the RTCRF (clinical trial observation mode) model were proposed. Our study enriches the theoretical research on robustness in this field.


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