Author(s)

Zongliang Zhao ¹, Yizhi Gao ¹, Hong Yu ¹

Affiliation(s)

¹ Shandong Jiaotong University, Jinan, Shandong, China

Corresponding Author

Zongliang Zhao

ABSTRACT

Nuclear weapons are immensely deadly weapons capable of releasing energy from nuclear reactions, including hydrogen bombs, atomic bombs, neutron bombastic.Nuclear weapons are extremely destructive, and their radiation and explosive power cause irreversible ecological damage. To better grasp the current situation and future trend of nuclear weapons globally and to protect the ecological environment of the earth, we built a BP neural network model and a time series model to predict the number of nuclear weapons possessing countries and the total number of nuclear weapons based on the existing number of nuclear weapons in each country in the world. After that, we modeled the detonation of nuclear weapons in different locations to analyze the damage level of nuclear weapons in different regions and to derive the limit of the number of nuclear weapons. The modeling results are combined to make recommendations for countries around the world to promote nuclear energy security development and world peace.

KEYWORDS

BP neural networks, time series models, ecological conservation, nuclear energy

CITE THIS PAPER

Zongliang Zhao, Yizhi Gao, Hong Yu, Study on Energy Limitation Based on Neural Network and ARMA. Environment, Resource and Ecology Journal (2023) Vol. 7: 10-17. DOI: http://dx.doi.org/10.23977/erej.2023.070202.

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