首页|Fuzzy Quantum Group Decision Making and Its Application in Meteorological Disaster Emergency
Fuzzy Quantum Group Decision Making and Its Application in Meteorological Disaster Emergency
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NETL
NSTL
IEEE
This article proposes a quantum group decision model that integrates intuitionistic fuzzy sets to represent the uncertainty of meteorological disaster information, addressing both vagueness and probabilistic uncertainty. This makes it particularly suitable for modeling the complex and dynamic decision-making processes during emergency responses. The model employs regret theory for attribute weight determination and constructs a quantum-like Bayesian network (QLBN), where Deng entropy is applied to measure the mutual interference effects among decision-makers. Decision-makers' weights are determined using grey relational analysis and incorporated as the initial layer in the Bayesian network. The conditional probabilities within the QLBN are derived by integrating attribute weights and regret utility functions, and the alternatives are ranked based on their final quantum probabilities. The effectiveness and stability of the model are demonstrated through its application in emergency alternative selection for meteorological disasters, confirmed by sensitivity and comparison analyzes.
School of Management Science and Engineering, Research Institute for Risk Governance and Emergency Decision-Making, Nanjing University of Information Science and Technology, Nanjing, China
Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain
NETL
NSTL
IEEE
