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Updated: Jul 6, 2025

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
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Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

Published on: July 1, 2014

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一个新的多区域碳排放预测模型,基于多变量信息融合机制和混合时空图形卷积网络

Zhen Shao1, Shina Gao2, Kaile Zhou3

  • 1School of Management, Hefei University of Technology, Hefei, 230009, China; Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, Anhui, 230009, China; Philosophy and Social Sciences Laboratory of Data Science and Smart Society Governance, Hefei University of Technology, Ministry of Education, Hefei, 230009, China.

Journal of environmental management
|January 10, 2024
PubMed
概括

本研究引入了一个新的图形学习框架,用于准确的短期碳排放预测 (CEP). 混合模型显著提高了趋势预测的准确性,有助于有效的减排政策.

关键词:
属性增强的动态多式联运GCN.多变量信息融合机制多变量信息融合机制平行堆叠的TCNs是平行堆叠的.短期多区域碳排放预测

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