A model for STIRPAT-based fusion predictive analytics

Yuyang Chen

doi:10.1117/12.3011497

7 December 2023 A model for STIRPAT-based fusion predictive analytics

Yuyang Chen

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 129413R (2023) https://doi.org/10.1117/12.3011497
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

In this paper, a model for STIRPAT-based fusion predictive analytics is proposed by building ARIMA time series model, BCC model, data envelopment analysis model, system dynamics model and STIRPAT model. The model solves the problem of predicting and analyzing heterogeneous data. This paper uses data such as IHSMarkit analysis reports and related patents to confirm the validity of the model. Finally, the model successfully predicts the time to achieve carbon neutrality in the Yangtze River Delta region and the amount of automobile ownership.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yuyang Chen "A model for STIRPAT-based fusion predictive analytics", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 129413R (7 December 2023); https://doi.org/10.1117/12.3011497

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