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RETRACTED ARTICLE: Research on the influencing factors of living energy consumption and carbon emissions based on spatiotemporal model

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This article was retracted on 25 March 2024

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Abstract

To explore the influencing factors of living energy consumption, this paper studies the carbon emissions of living energy consumption, and combines the spatiotemporal model to analyze the influencing factors of living energy consumption and carbon emissions. Moreover, this paper proposes a new carbon emission anomaly trajectory detection algorithm STOD for detecting spatiotemporal anomalies. The algorithm segments the complete carbon emission spatiotemporal trajectory and merges the carbon emission trajectory segments that meet the conditions according to the definition. In addition, this paper obtains the abnormal trajectory segment and abnormal trajectory of carbon emissions by calculating three different metrics. The proposed model obtains the outcome of 91.45 during the evaluation of living energy consumption carbon emission analysis based on the spatiotemporal model. The experimental study shows that the carbon emission analysis based on the spatiotemporal model proposed in this paper has a better effect.

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Enquiries about data availability should be directed to the authors.

Change history

Abbreviations

EKC:

Environmental Kuznets curve

OV:

Overlapping volume

STOD:

Spatial–temporal trajectory outlier detection

MBB:

Minimum bounding box

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Acknowledgements

Fund Project: soft science research program of Henan Province in 2022, research on the driving mechanism of low-carbon cycle development in rural areas of Henan driven by “Three Transformations”, Project Number: 222400410519.

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Authors and Affiliations

  1. Business School, Xuchang University, Xuchang, 461000, Henan, China

    Yang Zhimao

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  1. Yang Zhimao
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Correspondence to Yang Zhimao.

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This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1007/s10878-024-01138-6

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Zhimao, Y. RETRACTED ARTICLE: Research on the influencing factors of living energy consumption and carbon emissions based on spatiotemporal model. J Comb Optim 45, 25 (2023). https://doi.org/10.1007/s10878-022-00958-8

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  • DOI: https://doi.org/10.1007/s10878-022-00958-8

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