Selection of carbon emissions control industries in China: An approach based on complex networks control perspective
Tài liệu tham khảo
Chen, 2017, Carbon emissions in China's industrial sectors, Resour. Conserv. Recycl., 117, 264, 10.1016/j.resconrec.2016.10.008
Seo, 2015, Embodied carbon of building products during their supply chains: case study of aluminum window in Australia, Resour. Conserv. Recycl., 105, 160, 10.1016/j.resconrec.2015.10.024
Wang, 2013, Carbon dioxide mitigation target of China in 2020 and key economic sectors, Energy Policy, 58, 90, 10.1016/j.enpol.2013.02.038
Guo, 2018, The key sectors for energy conservation and carbon emissions reduction in China: evidence from the input-output method, J. Clean. Prod., 179, 180, 10.1016/j.jclepro.2018.01.080
Shen, 2018, A driving–driven perspective on the key carbon emission sectors in China, Nat. Hazards, 93, 349, 10.1007/s11069-018-3304-1
Yuan, 2020, Identification of key carbon emission sectors and analysis of emission effects in China, Sustainability, 12, 8673, 10.3390/su12208673
Shi, 2019, Tracing carbon emissions embodied in 2012 Chinese supply chains, J. Clean. Prod., 226, 28, 10.1016/j.jclepro.2019.04.015
Wen, 2020, Study on carbon transfer and carbon emission critical paths in China: I-O analysis with multidimensional analytical framework, Environ. Sci. Pollut. Res., 27, 9733, 10.1007/s11356-019-07549-x
Wang, 2017, Controlling embedded carbon emissions of sectors along the supply chains: a perspective of the power-of-pull approach, Appl. Energy, 206, 1544, 10.1016/j.apenergy.2017.09.108
Ma, 2019, Structural analysis of indirect carbon emissions embodied in intermediate input between Chinese sectors: a complex network approach, Environ. Sci. Pollut. Res., 26, 17591, 10.1007/s11356-019-05053-w
Wang, 2021, Structural evolution of China's intersectoral embodied carbon emission flow network, Environ. Sci. Pollut. Res., 28, 21145, 10.1007/s11356-020-11882-x
Lin, 1974, Structural controllability, IEEE Trans. Automat. Contr., 19, 201, 10.1109/TAC.1974.1100557
Liu, 2011, Controllability of complex networks, Nature, 473, 167, 10.1038/nature10011
Yuan, 2013, Exact controllability of complex networks, Nat. Commun., 4, 3447, 10.1038/ncomms3447
Jia, 2013, Control capacity and a random sampling method in exploring controllability of complex networks, Sci. Rep., 3, 2354, 10.1038/srep02354
Olshevsky, 2014, Minimal controllability problems, IEEE Trans. Control. Netw. Syst., 1, 249, 10.1109/TCNS.2014.2337974
Li, 2019, Minimum cost control of directed networks with selectable control inputs, IEEE Trans. Cybern., 49, 4431, 10.1109/TCYB.2018.2868507
Li, 2020, Target control of directed networks based on network flow problems, IEEE Trans. Control. Netw. Syst., 7, 673, 10.1109/TCNS.2019.2939641
Li, 2020, Target control and expandable target control of complex networks, J. Franklin Inst., 357, 3541, 10.1016/j.jfranklin.2019.11.064
Song, 2021, Target controllability of two-layer multiplex networks based on network flow theory, IEEE Trans. Cybern., 51, 2699, 10.1109/TCYB.2019.2906700
Gao, 2021, Optimal target control of complex networks with selectable inputs, IEEE Trans. Control. Netw. Syst., 8, 212, 10.1109/TCNS.2020.3024318
Rajapakse, 2011, Dynamics and control of state-dependent network for probing denomic organization, Proc. Natl. Acad. Sci. USA, 108, 17257, 10.1073/pnas.1113249108
Csermely, 2013, Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review, Pharmacol. Ther., 138, 333, 10.1016/j.pharmthera.2013.01.016
Wuchty, 2014, Controllability in protein interaction network, Proc. Natl. Acad. Sci. USA, 111, 7156, 10.1073/pnas.1311231111
Wang, 2015, Diversified control paths: a significant way disease genes perturb the human regulatory network, PLoS ONE, 10
Li, 2019, Control principles for complex biological networks, Brief. Bioinformatics, 20, 2253, 10.1093/bib/bby088
Delpini, 2013, Evolution of controllability in interbank networks, Sci. Rep., 3, 1626, 10.1038/srep01626
Matthews, 2008, The importance of carbon footprint estimation boundaries, Environ. Sci. Technol., 42, 5839, 10.1021/es703112w
Zhao, 2017, Simulation of industrial carbon emissions and its reduction in china based on input-output model, J. Nat. Resour., 32, 1528
Fan, 2010, Estimating the macroeconomic cost of CO2 emission abatement in China based on multi-objective programming, Adv. Climate Change Res., 6, 130
Jiang, 2018, Robust estimation and application of shadow price of CO2: evidence from China, J. Manage.World, 34, 32
Liu, 2012, Control centrality and hierarchical structure in complex networks, PLoS ONE, 7, e44459, 10.1371/journal.pone.0044459
Yin, 2015, Controllability and algorithma of complex networks, J. Syst. Sci. Math. Sci., 35, 1255
Zhou, 2016, Mechanism of carbon intensity reduction and optimization design of its industrial allocation, J.World Econ., 168
Baležentis, 2021, Exploring the limits for increasing energy efficiency in the residential sector of the European Union: insights from the rebound effect, Energy Policy, 149, 10.1016/j.enpol.2020.112063
Li, 2021, Multi-step least squares support vector machine modeling approach for forecasting short-term electricity demand with application, Neural Comput. Appl., 33, 301, 10.1007/s00521-020-04996-3