Work

Spatio-temporal grey Bernoulli model for green development of marine economy forecasting

Year: 2026

Type: article

Abstract: The sustainable development of the marine economy is inseparable from green development. However, the spatial correlations and dynamic evolution of green development present significant forecasting challenges. To address this, this paper first constructs an evaluation index system for the green development of marine economy based on the Driver-Pressure-State-Impact-Response ( DPSIR ) framework. Furthermore, the grey Bernoulli model is improved in both spatial and temporal dimensions for forecasting purposes. Interaction terms between spatial distance matrices and variables are introduced to capture spatial correlations, while a time-varying component is incorporated to reflect dynamic evolution. These enhancements enable the model to more effectively characterize the spatial, temporal, and nonlinear features of the green development of marine economy. Additionally, the model’s hyperparameters and weighting coefficients are optimized using the whale optimization algorithm. For validation, an empirical study is conducted across China’s 11 coastal provinces and municipalities. Systematic analyses show that the proposed model has high predictive accuracy. Robustness tests and sensitivity analysis further confirm that the model demonstrates excellent stability, reliability, and generalization capability.

Source: Engineering Applications of Artificial Intelligence

DOI: 10.1016/j.engappai.2026.113984

Authors: Na Li, Xuemei Li, Song Ding

Institutions: Ocean University of China, Zhejiang University of Finance and Economics

Language: English

Topic: Grey System Theory Applications

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDGs: Life below water, Climate action, Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $3,200