Evaluation and Prediction of the Future Development of Nuclear Weapons in the World Based on AHP and Neural Network

Pengyu Zhou; Boao Li; Shizhe Wang

doi:10.54097/hset.v50i.8554

Authors

Pengyu Zhou
Boao Li
Shizhe Wang

DOI:

https://doi.org/10.54097/hset.v50i.8554

Keywords:

Development of nuclear weapons; AHP; BP neural network; Cellular automata; TOPSIS.

Abstract

This paper first establishes a BP neural network model based on the steepest descent method to predict the number of nuclear weapon states in the next 100 years. Combining the AHP analytic hierarchy process model, it predicts the countries most likely to possess nuclear weapons in the next 100 years. Then, a linear regression method is used to predict the total number of nuclear weapons in 2123. Then calculate the killing range of nuclear weapons and establish an explosion location model. Finally, a model is established using cellular automata to determine the minimum number of nuclear weapons required to destroy the human survival environment, and to derive the limit range of the number of nuclear weapons. Finally, we describe our research results and propose some suggestions for the common destiny of all mankind.

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