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Study on the spatial and temporal evolution of industrial carbon emission efficiency and influencing factors based on improved Adaboost regression algorithm

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Mirza, F. M.,& Kanwal, A. (2017). Energy consumption, carbon emissions and economic growth in Pakistan: Dynamic causality analysis. Renewable and Sustainable Energy Reviews, 72, 1233-1240. Search in Google Scholar

Shahzad, S. J. H., Kumar, R. R., Zakaria, M., & Hurr, M. (2017). Carbon emission, energy consumption, trade openness and financial development in Pakistan: a revisit. Renewable and Sustainable Energy Reviews, 70, 185-192. Search in Google Scholar

Anser, M. K., Hanif, I., Alharthi, M., & Chaudhry, I. S. (2020). Impact of fossil fuels, renewable energy consumption and industrial growth on carbon emissions in Latin American and Caribbean economies. Atmósfera, 33(3), 201-213. Search in Google Scholar

Rahman, M. M., &Kashem, M. A. (2017). Carbon emissions, energy consumption and industrial growth in bangladesh: empirical evidence from ardl cointegration and granger causality analysis. Energy Policy, 110(nov.), 600-608. Search in Google Scholar

Ali, M. U., Zhimin, G., Asmi, F., Xue, Z., & Muhammad, R. (2021). The nexus between environmental degradation and industrial development in Pakistan and roles of financial development and fossil fuel. Environmental Progress & Sustainable Energy, 40(4), e13621. Search in Google Scholar

Wei, W., & Wang, Z. (2021). Impact of industrial air pollution on agricultural production. Atmosphere, 12(5), 639. Search in Google Scholar

Wu, Y., Zheng, H., Li, Y., Delang, C. O.,&Qian, J. (2021). Carbon productivity and mitigation: evidence from industrial development and urbanization in the central and western regions of china. Sustainability, 13. Search in Google Scholar

Khan, A. A., Khan, S. U., Ali, M., Safi, A., Gao, Y., & Ali, M., et al. (2022). Role of institutional quality and renewable energy consumption in achieving carbon neutrality: case study of g-7 economies. Science of The Total Environment, 814, 152797-. Search in Google Scholar

Peng, W., Yang, J., Lu, X., & Mauzerall, D. L. (2018). Potential co-benefits of electrification for air quality, health, and co2 mitigation in 2030 china. Applied Energy, 218(MAY15), 511-519. Search in Google Scholar

Zhang, F., Jin, G., Li, J., Wang, C., & Xu, N. (2020). Study on dynamic total factor carbon emission efficiency in china’s urban agglomerations. Sustainability, 12. Search in Google Scholar

Chen, Y., Yao, Z., & Zhong, K. (2022). Do environmental regulations of carbon emissions and air pollution foster green technology innovation: evidence from china’s prefecture-level cities. Journal of cleaner production, (May 20), 350. Search in Google Scholar

Cui, Y., Khan, S. U., Deng, Y., & Zhao, M. (2022). Spatiotemporal heterogeneity, convergence and its impact factors: perspective of carbon emission intensity and carbon emission per capita considering carbon sink effect. Environmental Impact Assessment Review, 92, 106699-. Search in Google Scholar

Qin, Q., Liu, Y., Li, X., & Li, H. (2017). A multi-criteria decision analysis model for carbon emission quota allocation in china’s east coastal areas: efficiency and equity. Journal of Cleaner Production, 168(Dec.1), 410-419. Search in Google Scholar

Meng, Min Fu, Yanan, Wang, & Tianyu, et al. (2017). Analysis of low-carbon economy efficiency of chinese industrial sectors based on a ram model with undesirable outputs. Sustainability. Search in Google Scholar

Yan, D., Lei, Y., Li, L., & Song, W. (2017). Carbon emission efficiency and spatial clustering analyses in china’s thermal power industry: evidence from the provincial level. Journal of Cleaner Production, 156(jul.10), 518-527. Search in Google Scholar

Zeng, L., Lu, H., Liu, Y., Zhou, Y., & Hu. (2019). Analysis of regional differences and influencing factors on china’s carbon emission efficiency in 2005–2015. Energies, 12(16), 3081. Search in Google Scholar

Yha, B., Chang, L., Zga, B., & Kz, C. (2018). Carbon emission analysis and evaluation of industrial departments in china: an improved environmental dea cross model based on information entropy. Journal of Environmental Management, 205, 298-307. Search in Google Scholar

Zhang, S., Fu, Q., &Xiao, W. (2017). Advertisement click-through rate prediction based on the weighted-elm and adaboost algorithm.Scientific Programming, 2017(PT.2), 2938369.1-2938369.8. Search in Google Scholar

Andrey, Kim, Yongsoo, Song, Miran, & Keewoo, et al. (2018). Logistic regression model training based on the approximate homomorphic encryption. Bmc Medical Genomics. Search in Google Scholar

Chu, J. F., Wu, J., & Song, M. L. (2018). An sbm-dea model with parallel computing design for environmental efficiency evaluation in the big data context: a transportation system application. Annals of Operations Research, 270(1), 105-124. Search in Google Scholar

Aghadadashi, V., Molaei, S., Mehdinia, A., Mohammadi, J., Moeinaddini, M., & Bakhtiari, A. R. (2019). Using gis, geostatistics and fuzzy logic to study spatial structure of sedimentary total pahs and potential eco-risks; an eastern persian gulf case study. Marine pollution bulletin, 149(Dec.), 110489.1-110489.12. Search in Google Scholar

Kwon, Y. R., & Lee, B. C. (2017). A mixed element based on lagrange multiplier method for modified couple stress theory. Computational Mechanics, 59(1), 1-12. Search in Google Scholar

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Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics