Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

December 2, 2023


Pages


DOI

Article

Analyzing the Importance of International Law in Current International Relations Based on Linear Programming Models

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Authors

Siquan Qin Affiliation:
School of Politics and Law, Baotou Teachers’ College, Baotou, Inner Mongolia, 014030, China.


Abstract

International law is mainly the law between countries, which is the code of conduct for countries to conduct international interactions, and this paper researches the role of international law in international relations interactions. First of all, this paper combines the fuzzy set on the basis of the classical linear regression model algorithm, establishes the fuzzy linear programming model, and explores the fuzzy correlation analysis. Then, taking EU law as an example, the role of EU law in EU relations is analyzed through the theory of EU law, EU and the role of EU law in the EU embodied. Finally, based on the role of EU law, the importance of international law in international relations is studied through a fuzzy linear programming model, and the role of strengthening international law is considered. The results show that the countries consider the legitimacy of EU law to be above 0.9, and the countries’ participation in EU law also ranges from 0.9 to 1.0, and the countries’ self-identification increases by about 0.1 to 0.2 after the enactment of EU law. The correlation coefficients of international law on the construction of the identities of the 10 countries are all greater than 0.75, and the interests of the countries have increased by about 2.3, and international law promotes the order of international relations.


Keywords

Linear regression modeling, Fuzzy sets, Fuzzy linear programming, International law, International relations, 68Q05


Citation

Qin, S. (2023). Analyzing the importance of international law in current international relations based on linear programming models. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.01316
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