An unbiased non-homogeneous grey forecasting model and its applications DOI
C. C. Li,

Youjun Chen,

Yanhui Xiang

et al.

Applied Mathematical Modelling, Journal Year: 2024, Volume and Issue: 137, P. 115677 - 115677

Published: Sept. 6, 2024

Language: Английский

Multi-step carbon emissions forecasting using an interpretable framework of new data preprocessing techniques and improved grey multivariable convolution model DOI
Song Ding, Juntao Ye, Zhijian Cai

et al.

Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 208, P. 123720 - 123720

Published: Sept. 4, 2024

Language: Английский

Citations

8
A novel intervention effect-based quadratic time-varying nonlinear discrete grey model for forecasting carbon emissions intensity DOI Creative Commons
Ye Li, Liping Fang, Yaoguo Dang

et al.

Information Sciences, Journal Year: 2024, Volume and Issue: 675, P. 120711 - 120711

Published: May 7, 2024

In the context of severe global warming, accurately exploring trend carbon emissions intensity (CEI) changes is great significance for mitigating climate change issues. The implementation China's Carbon Emissions Trading Scheme (ETS) in 2013 a policy intervention aimed at influencing CEI. impact events makes forecasting complex problem, which poses significant challenges to construction models. We first develop quadratic time-varying nonlinear discrete grey model (QDNDGM(1,1)) assess effect ETS policy. Then, novel effect-based (IE-QDNDGM(1,1)) developed conduct prediction under effect, including an term. Whale Optimization Algorithm (WOA) used calculate parameter. China and find that it can indeed reduce verify IE-QDNDGM(1,1) model's superiority by comparing its predictive performance with three models, one statistical technique, artificial intelligence model. comparative study shows proposed excellent fitting performance. An ablation experiment conducted validate design IE-QDNDGM(1,1). Policy implications are discussed.

Language: Английский

Citations

5
How does green technology innovation affect urban carbon emissions? Evidence from Chinese cities DOI
Xiaojuan Lu, Zeng Lü

Energy and Buildings, Journal Year: 2024, Volume and Issue: 325, P. 115025 - 115025

Published: Nov. 7, 2024

Language: Английский

Citations

5
A novel multivariate nonlinear time-delayed grey model for forecasting electricity consumption DOI
Wen-Ze Wu, Naiming Xie

Engineering Applications of Artificial Intelligence, Journal Year: 2025, Volume and Issue: 149, P. 110452 - 110452

Published: March 11, 2025

Language: Английский

Citations

0
A novel nonlinear time-varying grey prediction framework for green transformation of manufacturing industry: Modeling of a non-equidistant perspective DOI
Shiwei Zhou, Yufeng Zhao, Xuemei Li

et al.

Computers & Industrial Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 111068 - 111068

Published: March 1, 2025

Language: Английский

Citations

0
Prediction of seasonal variation pollutant sequence based on binomial coupled nonlinear grey Bernoulli model DOI
Shuai Huang, Lihua Ning, Jiayi An

et al.

Grey Systems Theory and Application, Journal Year: 2025, Volume and Issue: unknown

Published: April 9, 2025

Purpose The traditional grey Bernoulli model often faces limitations when applied to pollutant concentration series, which may exhibit complex seasonal trends and varying data types. To address these challenges, we propose a structural extension of the by integrating binomial equation. This allows for more flexible framework suitable diverse datasets, especially those related environmental pollution. Design/methodology/approach First, time series is decomposed into four relatively stable sub-sequences. Binomial nonlinear models are then integrated predict prediction formula proposed derived directly from definition equation rather than solutions differential equation, thereby minimizing systematic errors. particle swarm optimization algorithm used estimate parameters, while least squares method linear parameters model. Findings BNGBM(1,1) forecast air quality index (AQI), sulfur dioxide (SO 2 ) particulate matter (PM2.5) seven major regions in China. results show that has superior accuracy compared competing models. predicts variations three pollution indicators selected period 2023–2024. concentrations all indices will decrease at different rates. Originality/value well suited sequences exhibiting quasi-exponential growth, whereas polynomial appropriate characterized saturated growth. integration two extends their applicability. In empirical study, despite development China, forecasting demonstrates effective performance indicators.

Language: Английский

Citations

0
An innovative nonlinear grey system model with generalized fractional operators and its application DOI

Jianguo Zheng,

Meixin Huang,

Jiale Zhang

et al.

Alexandria Engineering Journal, Journal Year: 2025, Volume and Issue: 125, P. 463 - 479

Published: April 22, 2025

Language: Английский

Citations

0
Bottom-up discrete systematic modelling for analysis and prediction of future trends for land-sea environmental pollution systems DOI

Kedong Yin,

Yufeng Zhao, Xuemei Li

et al.

Applied Mathematical Modelling, Journal Year: 2024, Volume and Issue: unknown, P. 115830 - 115830

Published: Nov. 1, 2024

Language: Английский

Citations

3
A novel information enhanced Grey Lotka–Volterra model driven by system mechanism and data for energy forecasting of WEET project in China DOI

Tianyao Duan,

Huan Guo, Qi Xiao

et al.

Energy, Journal Year: 2024, Volume and Issue: 304, P. 132176 - 132176

Published: June 25, 2024

Language: Английский

Citations

2
An unbiased non-homogeneous grey forecasting model and its applications DOI
C. C. Li,

Youjun Chen,

Yanhui Xiang

et al.

Applied Mathematical Modelling, Journal Year: 2024, Volume and Issue: 137, P. 115677 - 115677

Published: Sept. 6, 2024

Language: Английский

Citations

2