A Dynamic Weight Determination Approach Based on the Intuitionistic Fuzzy Bayesian Network and Its Application to Emergency Decision Making

2018 ◽  
Vol 26 (4) ◽  
pp. 1893-1907 ◽  
Author(s):  
Zhinan Hao ◽  
Zeshui Xu ◽  
Hua Zhao ◽  
Hamido Fujita
Keyword(s):  
Decision Making ◽  
Bayesian Network ◽  
Intuitionistic Fuzzy ◽  
Dynamic Weight ◽  
Emergency Decision Making ◽  
Emergency Decision

scholarly journals Case Reasoning-Based Emergency Decision Making for Oil and Gas Accidents

2020 ◽  
Vol 15 (7) ◽  
pp. 981-990
Author(s):  
Ruifang La ◽  
Zaixu Zhang ◽  
Pengfei Bai ◽  
◽  
◽  
...  
Keyword(s):  
Decision Making ◽  
Bayesian Network ◽  
Oil And Gas ◽  
Search Space ◽  
Case Based Reasoning ◽  
Emergency Plans ◽  
Oil Pipeline ◽  
Emergency Decision Making ◽  
Disaster Monitoring ◽  
Emergency Decision

Throughout the digitization of the petrochemical industry, the Beidou technology-based disaster monitoring, evaluation, and early warning network system has supported emergency decision making for oil and gas accidents. Many problems arise throughout the emergency decision-making process during oil–gas accidents, such as the limited time for decision making, high complexity, and inadequate emergency plans. Targeting these issues, we propose the construction of a case library using a Bayesian network. This way, when a new accident occurs, its similarity and deviation indexes could be matched against those of historical cases registered in the database. As such, the candidate cases are adjusted using a case combination and pruning method, yielding the final qualified case model. A case verification of the “11.22” Sinopec Oil pipeline leak and explosion in Qingdao reveals that the proposed method only requires an oil and gas accident database to be built in advance, eliminating the need for sampling data to make decisions, and reducing the search space. Using the proposed case-based reasoning, historical data and experience regarding oil and gas emergency decisions can be activated and reused, which would greatly improve the modeling efficiency of the Bayesian network.

Decision-Making Model for Ranking Earthquake Emergency Events Based on Intuitionistic Fuzzy Sets

2012 ◽  
Vol 204-208 ◽  
pp. 2488-2493
Author(s):  
Feng Shan Wang ◽  
Li Fa Wu ◽  
Quan Bing Rong ◽  
Hong Jun Zhang
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Interval Estimation ◽  
Intuitionistic Fuzzy Sets ◽  
Ranking Problem ◽  
Fuzzy Matrix ◽  
Intuitionistic Fuzzy ◽  
Emergency Decision Making ◽  
Emergency Events ◽  
Emergency Decision

To ravel out the difficulty in the expression and measurement of Non-subjected Information in earthquake emergency decision-making under fuzzy environmental conditions, a ranking method was put forward for earthquake emergency events on Intuitionistic Fuzzy Sets. Via the explanation about the concept of Intuitionistic Fuzzy Sets, intuitionistic fuzzy matrix and its interval estimation was established for the set of the earthquake emergency events, and the positive and negative ideal intuitionistic fuzzy earthquake emergency was determined; Through defining the distance calculation about subjected, non-subjected and hesitated degree, and respectively comparing the distance from the emergency to the positive and negative ideal event, the superiority degree model was established for the earthquake emergency events, which further gained the sequence of the emergency event collection. Case showed that model effectively solved the ranking problem about earthquake emergency events, which provided one theory and method for scientific decision-making practice in shock resistance and disaster relief.

scholarly journals A New Multi-Attribute Emergency Decision-Making Algorithm Based on Intuitionistic Fuzzy Cross-Entropy and Comprehensive Grey Correlation Analysis

Entropy ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. 768
Author(s):  
Ping Li ◽  
Ying Ji ◽  
Zhong Wu ◽  
Shao-Jian Qu
Keyword(s):  
Decision Making ◽  
Correlation Analysis ◽  
Cross Entropy ◽  
Analysis Algorithm ◽  
Grey Correlation ◽  
Fuzzy Distance ◽  
Intuitionistic Fuzzy ◽  
Grey Correlation Analysis ◽  
Emergency Decision Making ◽  
Emergency Decision

Intuitionistic fuzzy distance measurement is an effective method to study multi-attribute emergency decision-making (MAEDM) problems. Unfortunately, the traditional intuitionistic fuzzy distance measurement method cannot accurately reflect the difference between membership and non-membership data, where it is easy to cause information confusion. Therefore, from the intuitionistic fuzzy number (IFN), this paper constructs a decision-making model based on intuitionistic fuzzy cross-entropy and a comprehensive grey correlation analysis algorithm. For the MAEDM problems of completely unknown and partially known attribute weights, this method establishes a grey correlation analysis algorithm based on the objective evaluation value and subjective preference value of decision makers (DMs), which makes up for the shortcomings of traditional model information loss and greatly improves the accuracy of MAEDM. Finally, taking the Wenchuan Earthquake on May 12th 2008 as a case study, this paper constructs and solves the ranking problem of shelters. Through the sensitivity comparison analysis, when the grey resolution coefficient increases from 0.4 to 1.0, the ranking result of building shelters remains stable. Compared to the traditional intuitionistic fuzzy distance, this method is shown to be more reliable.

An improved multi-criteria emergency decision-making method in environmental disasters

2021 ◽  
Author(s):  
Guang-Jun Jiang ◽  
Hong-Xia Chen ◽  
Hong-Hua Sun ◽  
Mohammad Yazdi ◽  
Arman Nedjati ◽  
...  
Keyword(s):  
Decision Making ◽  
Environmental Disasters ◽  
Emergency Decision Making ◽  
Emergency Decision

scholarly journals An Emergency Decision-Making Method for Urban Rainstorm Water-Logging: A China Study

2018 ◽  
Vol 10 (10) ◽  
pp. 3453 ◽  
Author(s):  
Jiyong Ding ◽  
Juefang Cai ◽  
Guangxiang Guo ◽  
Chen Chen
Keyword(s):  
Decision Making ◽  
Bayesian Analysis ◽  
Emergency Management ◽  
Utility Theory ◽  
Urban Traffic ◽  
Economic Losses ◽  
Water Logging ◽  
Multi Attribute Utility Theory ◽  
Emergency Decision Making ◽  
Emergency Decision

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.

scholarly journals Managing Non-Homogeneous Information and Experts’ Psychological Behavior in Group Emergency Decision Making

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

scholarly journals An Artificial Intelligence Fusion Model for Cardiac Emergency Decision Making: Application and Robustness Analysis

10.2196/19428 ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. e19428
Author(s):  
Liheng Gong ◽  
Xiao Zhang ◽  
Ling Li
Keyword(s):  
Decision Making ◽  
Medical Treatment ◽  
Coordination Mechanism ◽  
Theoretical Research ◽  
Medical Decision ◽  
Knowledge Reasoning ◽  
Emergency Medical ◽  
Emergency Decision Making ◽  
Emergency Decision ◽  
Cardiac Emergency

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.

Pythagorean probabilistic hesitant fuzzy aggregation operators and their application in decision-making

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bushra Batool ◽  
Saleem Abdullah ◽  
Shahzaib Ashraf ◽  
Mumtaz Ahmad
Keyword(s):  
Decision Making ◽  
Fuzzy Number ◽  
Weighted Average ◽  
Aggregation Operators ◽  
Content Type ◽  
Operational Laws ◽  
Fuzzy Aggregation ◽  
Emergency Decision Making ◽  
Emergency Decision ◽  
Established Technique

PurposeThis is mainly because the restrictive condition of intuitionistic hesitant fuzzy number (IHFN) is relaxed by the membership functions of Pythagorean probabilistic hesitant fuzzy number (PyPHFN), so the range of domain value of PyPHFN is greatly expanded. The paper aims to develop a novel decision-making technique based on aggregation operators under PyPHFNs. For this, the authors propose Algebraic operational laws using algebraic norm for PyPHFNs. Furthermore, a list of aggregation operators, namely Pythagorean probabilistic hesitant fuzzy weighted average (PyPHFWA) operator, Pythagorean probabilistic hesitant fuzzy weighted geometric (PyPHFWG) operator, Pythagorean probabilistic hesitant fuzzy ordered weighted average (PyPHFOWA) operator, Pythagorean probabilistic hesitant fuzzy ordered weighted geometric (PyPHFOWG) operator, Pythagorean probabilistic hesitant fuzzy hybrid weighted average (PyPHFHWA) operator and Pythagorean probabilistic hesitant fuzzy hybrid weighted geometric (PyPHFHWG) operator, are proposed based on the defined algebraic operational laws. Also, interesting properties of these aggregation operators are discussed in detail.Design/methodology/approachPyPHFN is not only a generalization of the traditional IHFN, but also a more effective tool to deal with uncertain multi-attribute decision-making problems.FindingsIn addition, the authors design the algorithm to handle the uncertainty in emergency decision-making issues. At last, a numerical case study of coronavirus disease 2019 (COVID-19) as an emergency decision-making is introduced to show the implementation and validity of the established technique. Besides, the comparison of the existing and the proposed technique is established to show the effectiveness and validity of the established technique.Originality/valuePaper is original and not submitted elsewhere.

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