An international relations quantitative evaluation model (IRQEM) based on an integrated method

Author:

Ma Yaping12ORCID,Yao Mengjiao12,Yu Feng3,Xiao Xingyu4,Huang Lida5,Zhang Hui5,Deng Qing6

Affiliation:

1. School of Safety Science and Emergency Management Wuhan University of Technology Wuhan China

2. China Research Center for Emergency Management Wuhan University of Technology Wuhan China

3. School of International and Public Affairs Shanghai Jiao Tong University Shanghai China

4. Institute of Nuclear and New Energy Technology Tsinghua University Beijing China

5. School of Safety Science Tsinghua University Beijing China

6. Research Institute of Macro‐Safety Science University of Science and Technology Beijing Beijing China

Abstract

AbstractInternational relations (IR) have great uncertainty and instability. Bad IR or conflicts will bring about heavy economic losses and widespread social unrest domestically and internationally. The accurate prediction for bilateral relations can support decision making for timely responses, which will be used to find ways to maintain development in the complex international situation. An international relations quantitative evaluation model (IRQEM) is proposed by integrating a variety of research models and methods like the interpretative structural modeling method (ISM), Bayesian network (BN) model, the Bayesian search (BS), and the expectation–maximization (EM) algorithm, which is novel for IR research. Factors from several different fields are identified as BN nodes. Each node is assigned different state values. The hierarchical structure of these BN nodes is obtained by ISM. The data collection of 192 cases is used to construct the BN model by GeNIe 4.0. The IRQEM can be used to evaluate the influence of emergencies on IR. The critical factors of IR also can be explored through our proposed model. Results show that the prediction of bilateral relations under emergencies can be realized by updating the indicator set when emergencies occur. The capability to anticipate threats of IR changes is advanced by optimizing the reporting information of IR forecasting through a combination of qualitative and quantitative methods, charts, and texts. Relevant analysis results can provide support for national security decision making.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Wiley

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