Research on the Transformation of Regional Economic Green Development Model Driven by Technological Innovation
DOI:
https://doi.org/10.54097/vr28gn48Keywords:
Technological innovation, regional economy, green development, graph attention network, algorithm comparison, policy simulation.Abstract
This paper, addressing the needs of high-quality regional economic development and green and low-carbon governance, constructs a computational analysis framework for the synergistic effects of technological innovation, industrial structure, energy efficiency, carbon emission constraints, and economic quality. It also proposes a graph attention algorithm, TIGT-GA, for driving green transformation through technological innovation. This algorithm treats regions as graph nodes and constructs technological cooperation, industrial linkages, energy structure similarities, and policy synergies as graph edges. It introduces green constraint factors and a gated temporal state update mechanism into the traditional graph attention mechanism, thereby achieving prediction of regional green transformation index, level identification, and policy scenario simulation. Experiments are conducted using panel structure data from 2013 to 2023 for 30 regions, and comparisons are made with algorithms such as entropy-weighted TOPSIS, SVR, random forest, XGBoost, BP neural network, LSTM, and ordinary GAT. The results show that TIGT-GA has an RMSE of 0.041, an MAE of 0.028, an R² of 0.934, and a rating accuracy of 91.6%, which is 28.07% lower than the RMSE of ordinary GAT and 33.87% lower than XGBoost. Policy simulation results show that when R&D intensity increases by 20%, the regional average green transition index increases from 0.612 to 0.684, an increase of 11.76%; when R&D investment, digital infrastructure, and green finance support are synergistically improved, the green transition index reaches 0.712, and the carbon emission intensity per unit of GDP decreases by 10.27%. The research indicates that technological innovation can significantly promote regional green transformation, but its effect needs to be released through the synergy of technology diffusion, digital infrastructure, industrial upgrading, and green policies.
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