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An innovative prediction algorithm based on grey modeling theory and the marine predators algorithm for short-term carbon dioxide emissions in China

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成果类型:
期刊论文
作者:
Chong Liu;Wen-Ze Wu;Wanli Xie;Sheng Shi;Hegui Zhu*
通讯作者:
Hegui Zhu
作者机构:
[Chong Liu; Sheng Shi; Hegui Zhu] College of Sciences, Northeastern University, Shenyang, 110819, China
[Wen-Ze Wu] School of Economics and Business Administration, Central China Normal University, Wuhan 430079, China
[Wanli Xie] Institute of EduInfo Science and Engineering, Nanjing Normal University, Nanjing 210097, China
通讯机构:
[Hegui Zhu] C
College of Sciences, Northeastern University, Shenyang, 110819, China
语种:
英文
期刊:
Engineering Applications of Artificial Intelligence
ISSN:
0952-1976
年:
2024
卷:
137
页码:
109066
机构署名:
本校为其他机构
院系归属:
经济与工商管理学院
摘要:
To accurately predict China’s carbon dioxide emissions, this paper constructs an innovative prediction algorithm based on the marine predators algorithm and a new discrete nonlinear grey Bernoulli model with fractional-order accumulation operation. In this prediction algorithm, the new model is used to complete the modeling task of nonlinear time series, and the marine predators algorithm is used to facilitate the solution process of model. It is found that the proposed model satisfies both unbiasedness and uniformity, underscoring its superio...

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