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Qiang Zhang

Not to be confused with: Qiang Zhang

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

  1. Qiang Zhang & Ping Chen, 2020. "Optimal Reinsurance and Investment Strategy for an Insurer in a Model with Delay and Jumps," Methodology and Computing in Applied Probability, Springer, vol. 22(2), pages 777-801, June.

    Cited by:

    1. Ning Bin & Huainian Zhu & Chengke Zhang, 2023. "Stochastic Differential Games on Optimal Investment and Reinsurance Strategy with Delay Under the CEV Model," Methodology and Computing in Applied Probability, Springer, vol. 25(2), pages 1-27, June.
    2. Yuan, Yu & Han, Xia & Liang, Zhibin & Yuen, Kam Chuen, 2023. "Optimal reinsurance-investment strategy with thinning dependence and delay factors under mean-variance framework," European Journal of Operational Research, Elsevier, vol. 311(2), pages 581-595.
    3. Peng, Xingchun & Chen, Fenge & Wang, Wenyuan, 2021. "Robust optimal investment and reinsurance for an insurer with inside information," Insurance: Mathematics and Economics, Elsevier, vol. 96(C), pages 15-30.

  2. Lei Ge & Qiang Zhang, 2020. "Numerical Solutions to Optimal Portfolio Selection and Consumption Strategies under Stochastic Volatility," Complexity, Hindawi, vol. 2020, pages 1-16, July.

    Cited by:

    1. Yingting Miao & Qiang Zhang, 2023. "Optimal Investment and Consumption Strategies with General and Linear Transaction Costs under CRRA Utility," Papers 2304.07672, arXiv.org.

  3. Zhenyu Jiang & Nengxiang Ling & Zudi Lu & Dag Tj⊘stheim & Qiang Zhang, 2020. "On bandwidth choice for spatial data density estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(3), pages 817-840, July.

    Cited by:

    1. Zhang, Rongmao & Chan, Ngai Hang & Chi, Changxiong, 2023. "Nonparametric testing for the specification of spatial trend functions," Journal of Multivariate Analysis, Elsevier, vol. 196(C).

  4. Zhang, Qiang & Chen, Wenying, 2020. "Modeling China’s interprovincial electricity transmission under low carbon transition," Applied Energy, Elsevier, vol. 279(C).

    Cited by:

    1. Liu, Benxi & Liu, Tengyuan & Liao, Shengli & Lu, Jia & Cheng, Chuntian, 2023. "Short-term coordinated hybrid hydro-wind-solar optimal scheduling model considering multistage section restrictions," Renewable Energy, Elsevier, vol. 217(C).
    2. Xiao, Jin & Li, Guohao & Xie, Ling & Wang, Shouyang & Yu, Lean, 2021. "Decarbonizing China's power sector by 2030 with consideration of technological progress and cross-regional power transmission," Energy Policy, Elsevier, vol. 150(C).
    3. Jia, Zhijie & Wen, Shiyan & Wang, Yao, 2023. "Power coming from the sky: Economic benefits of inter-regional power transmission in China," Energy Economics, Elsevier, vol. 119(C).
    4. Yu, Zhongjue & Geng, Yong & Calzadilla, Alvaro & Bleischwitz, Raimund, 2022. "China's unconventional carbon emissions trading market: The impact of a rate-based cap in the power generation sector," Energy, Elsevier, vol. 255(C).
    5. Qiu, Shuo & Lei, Tian & Wu, Jiangtao & Bi, Shengshan, 2021. "Energy demand and supply planning of China through 2060," Energy, Elsevier, vol. 234(C).
    6. Jin, Jingliang & Wen, Qinglan & Cheng, Siqi & Qiu, Yaru & Zhang, Xianyue & Guo, Xiaojun, 2022. "Optimization of carbon emission reduction paths in the low-carbon power dispatching process," Renewable Energy, Elsevier, vol. 188(C), pages 425-436.
    7. Liu, Zhengguang & Guo, Zhiling & Song, Chenchen & Du, Ying & Chen, Qi & Chen, Yuntian & Zhang, Haoran, 2023. "Business model comparison of slum-based PV to realize low-cost and flexible power generation in city-level," Applied Energy, Elsevier, vol. 344(C).
    8. Feng Liu & Tao Lv & Yuan Meng & Xiaoran Hou & Jie Xu & Xu Deng, 2022. "Low-Carbon Transition Paths of Coal Power in China’s Provinces under the Context of the Carbon Trading Scheme," Sustainability, MDPI, vol. 14(15), pages 1-14, August.
    9. Yang, Yan-Shen & Xie, Bai-Chen & Tan, Xu, 2024. "Impact of green power trading mechanism on power generation and interregional transmission in China," Energy Policy, Elsevier, vol. 189(C).
    10. Zhang, Changbing & Cao, Wenzhe & Xie, Tingting & Wang, Chongxun & Shen, Chunhe & Wen, Xiankui & Mao, Cheng, 2022. "Operational characteristics and optimization of Hydro-PV power hybrid electricity system," Renewable Energy, Elsevier, vol. 200(C), pages 601-613.
    11. Jin, Yi & Behrens, Paul & Tukker, Arnold & Scherer, Laura, 2021. "The energy-water nexus of China’s interprovincial and seasonal electric power transmission," Applied Energy, Elsevier, vol. 286(C).
    12. Huang, Runyao & Shen, Ziheng & Wang, Hongtao & Xu, Jin & Ai, Zisheng & Zheng, Hongyuan & Liu, Runxi, 2021. "Evaluating the energy efficiency of wastewater treatment plants in the Yangtze River Delta: Perspectives on regional discrepancies," Applied Energy, Elsevier, vol. 297(C).
    13. Huaibo Yang & Chao Shi & Jianbo Li & Tianran Liu & Youwei Li & Yao Wang & Yueying Yang, 2022. "Has the Inter-Regional Power Transmission Promoted Economic Development? A Quantitative Assessment in China," Sustainability, MDPI, vol. 14(20), pages 1-13, October.
    14. Zhenyu Zhuo & Ershun Du & Ning Zhang & Chris P. Nielsen & Xi Lu & Jinyu Xiao & Jiawei Wu & Chongqing Kang, 2022. "Cost increase in the electricity supply to achieve carbon neutrality in China," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    15. Zhang, Chongchong & Cai, Xiangyu & Lin, Boqiang, 2023. "The low-carbon transition of China's power sector: Scale effect of grid upgrading," Energy, Elsevier, vol. 285(C).

  5. Xin-Bing Cheng & Meng-Qiang Zhao & Chi Chen & Amanda Pentecost & Kathleen Maleski & Tyler Mathis & Xue-Qiang Zhang & Qiang Zhang & Jianjun Jiang & Yury Gogotsi, 2017. "Nanodiamonds suppress the growth of lithium dendrites," Nature Communications, Nature, vol. 8(1), pages 1-9, December.

    Cited by:

    1. Yuxiang Xie & Yixin Huang & Yinggan Zhang & Tairui Wu & Shishi Liu & Miaolan Sun & Bruce Lee & Zhen Lin & Hui Chen & Peng Dai & Zheng Huang & Jian Yang & Chenguang Shi & Deyin Wu & Ling Huang & Yingji, 2023. "Surface modification using heptafluorobutyric acid to produce highly stable Li metal anodes," Nature Communications, Nature, vol. 14(1), pages 1-10, December.

  6. Yiyuan Zhou & Qiang Zhang, 2015. "Multiple-Machine Scheduling with Learning Effects and Cooperative Games," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-7, July.

    Cited by:

    1. Peng Liu & Xiaoli Wang, 2017. "Maximum Lateness Scheduling on Two-Person Cooperative Games with Variable Processing Times and Common Due Date," Journal of Optimization, Hindawi, vol. 2017, pages 1-7, April.

  7. Shao, Zhen & Gao, Fei & Zhang, Qiang & Yang, Shan-Lin, 2015. "Multivariate statistical and similarity measure based semiparametric modeling of the probability distribution: A novel approach to the case study of mid-long term electricity consumption forecasting i," Applied Energy, Elsevier, vol. 156(C), pages 502-518.

    Cited by:

    1. Lei Jiang & Ling Bai, 2017. "Revisiting the Granger Causality Relationship between Energy Consumption and Economic Growth in China: A Multi-Timescale Decomposition Approach," Sustainability, MDPI, vol. 9(12), pages 1-17, December.
    2. Shao, Zhen & Gao, Fei & Yang, Shan-Lin & Yu, Ben-gong, 2015. "A new semiparametric and EEMD based framework for mid-term electricity demand forecasting in China: Hidden characteristic extraction and probability density prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 876-889.
    3. Shao, Zhen & Chao, Fu & Yang, Shan-Lin & Zhou, Kai-Le, 2017. "A review of the decomposition methodology for extracting and identifying the fluctuation characteristics in electricity demand forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 123-136.
    4. Tang, Lei & Wang, Xifan & Wang, Xiuli & Shao, Chengcheng & Liu, Shiyu & Tian, Shijun, 2019. "Long-term electricity consumption forecasting based on expert prediction and fuzzy Bayesian theory," Energy, Elsevier, vol. 167(C), pages 1144-1154.
    5. Nafidi, A. & Gutiérrez, R. & Gutiérrez-Sánchez, R. & Ramos-Ábalos, E. & El Hachimi, S., 2016. "Modelling and predicting electricity consumption in Spain using the stochastic Gamma diffusion process with exogenous factors," Energy, Elsevier, vol. 113(C), pages 309-318.
    6. Hu, Huanling & Wang, Lin & Peng, Lu & Zeng, Yu-Rong, 2020. "Effective energy consumption forecasting using enhanced bagged echo state network," Energy, Elsevier, vol. 193(C).
    7. Xingcai Zhou & Jiangyan Wang, 2021. "Panel semiparametric quantile regression neural network for electricity consumption forecasting," Papers 2103.00711, arXiv.org.
    8. Shao, Zhen & Yang, ShanLin & Gao, Fei & Zhou, KaiLe & Lin, Peng, 2017. "A new electricity price prediction strategy using mutual information-based SVM-RFE classification," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 330-341.
    9. Jiang, Ping & Li, Ranran & Liu, Ningning & Gao, Yuyang, 2020. "A novel composite electricity demand forecasting framework by data processing and optimized support vector machine," Applied Energy, Elsevier, vol. 260(C).
    10. Rafael Sánchez-Durán & Julio Barbancho & Joaquín Luque, 2019. "Solar Energy Production for a Decarbonization Scenario in Spain," Sustainability, MDPI, vol. 11(24), pages 1-29, December.
    11. Gao, Tian & Niu, Dongxiao & Ji, Zhengsen & Sun, Lijie, 2022. "Mid-term electricity demand forecasting using improved variational mode decomposition and extreme learning machine optimized by sparrow search algorithm," Energy, Elsevier, vol. 261(PB).
    12. Yuan, Xiao-Chen & Sun, Xun & Zhao, Weigang & Mi, Zhifu & Wang, Bing & Wei, Yi-Ming, 2017. "Forecasting China’s regional energy demand by 2030: A Bayesian approach," Resources, Conservation & Recycling, Elsevier, vol. 127(C), pages 85-95.
    13. Paul Anton Verwiebe & Stephan Seim & Simon Burges & Lennart Schulz & Joachim Müller-Kirchenbauer, 2021. "Modeling Energy Demand—A Systematic Literature Review," Energies, MDPI, vol. 14(23), pages 1-58, November.
    14. Gerossier, Alexis & Barbier, Thibaut & Girard, Robin, 2017. "A novel method for decomposing electricity feeder load into elementary profiles from customer information," Applied Energy, Elsevier, vol. 203(C), pages 752-760.
    15. He, Yaoyao & Qin, Yang & Wang, Shuo & Wang, Xu & Wang, Chao, 2019. "Electricity consumption probability density forecasting method based on LASSO-Quantile Regression Neural Network," Applied Energy, Elsevier, vol. 233, pages 565-575.

  8. Yu, Zu-Guo & Leung, Yee & Chen, Yongqin David & Zhang, Qiang & Anh, Vo & Zhou, Yu, 2014. "Multifractal analyses of daily rainfall time series in Pearl River basin of China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 193-202.

    Cited by:

    1. Méndez-Gordillo, Alma Rosa & Campos-Amezcua, Rafael & Cadenas, Erasmo, 2022. "Wind speed forecasting using a hybrid model considering the turbulence of the airflow," Renewable Energy, Elsevier, vol. 196(C), pages 422-431.
    2. Sarker, Alivia & Mali, Provash, 2021. "Detrended multifractal characterization of Indian rainfall records," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    3. Lahmiri, Salim, 2015. "Long memory in international financial markets trends and short movements during 2008 financial crisis based on variational mode decomposition and detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 130-138.
    4. Morales Martínez, Jorge Luis & Segovia-Domínguez, Ignacio & Rodríguez, Israel Quiros & Horta-Rangel, Francisco Antonio & Sosa-Gómez, Guillermo, 2021. "A modified Multifractal Detrended Fluctuation Analysis (MFDFA) approach for multifractal analysis of precipitation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    5. Braga, A.C. & Alves, L.G.A. & Costa, L.S. & Ribeiro, A.A. & de Jesus, M.M.A. & Tateishi, A.A. & Ribeiro, H.V., 2016. "Characterization of river flow fluctuations via horizontal visibility graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 1003-1011.
    6. Adarsh Sankaran & Sagar Rohidas Chavan & Mumtaz Ali & Archana Devarajan Sindhu & Drisya Sasi Dharan & Muhammad Ismail Khan, 2021. "Spatiotemporal variability of multifractal properties of fineresolution daily gridded rainfall fields over India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 106(3), pages 1951-1979, April.

  9. Yang Lei & Shurong Li & Xiaodong Zhang & Qiang Zhang & Lanlei Guo, 2012. "Optimal Control of Polymer Flooding Based on Maximum Principle," Journal of Applied Mathematics, Hindawi, vol. 2012, pages 1-20, July.

    Cited by:

    1. Shurong Li & Yulei Ge & Yuhuan Shi, 2018. "Enhanced Oil Recovery for ASP Flooding Based on Biorthogonal Spatial-Temporal Wiener Modeling and Iterative Dynamic Programming," Complexity, Hindawi, vol. 2018, pages 1-19, October.

  10. Zhang, Qiang & Xu, Chong-Yu & Yu, Zuguo & Liu, Chun-Ling & Chen, Yongqin David, 2009. "Multifractal analysis of streamflow records of the East River basin (Pearl River), China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(6), pages 927-934.

    Cited by:

    1. Xinjun Tu & Vijay Singh & Xiaohong Chen & Lu Chen & Qiang Zhang & Yong Zhao, 2015. "Intra-annual Distribution of Streamflow and Individual Impacts of Climate Change and Human Activities in the Dongijang River Basin, China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2677-2695, June.
    2. Yu, Zu-Guo & Leung, Yee & Chen, Yongqin David & Zhang, Qiang & Anh, Vo & Zhou, Yu, 2014. "Multifractal analyses of daily rainfall time series in Pearl River basin of China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 193-202.
    3. Ozger, Mehmet, 2011. "Scaling characteristics of ocean wave height time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(6), pages 981-989.
    4. Telesca, Luciano & Lovallo, Michele & Lopez-Moreno, Ignacio & Vicente-Serrano, Sergio, 2012. "Investigation of scaling properties in monthly streamflow and Standardized Streamflow Index (SSI) time series in the Ebro basin (Spain)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1662-1678.
    5. He, Ling-Yun & Chen, Shu-Peng, 2010. "Are crude oil markets multifractal? Evidence from MF-DFA and MF-SSA perspectives," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3218-3229.
    6. Huang, Xu & Maçaira, Paula Medina & Hassani, Hossein & Cyrino Oliveira, Fernando Luiz & Dhesi, Gurjeet, 2019. "Hydrological natural inflow and climate variables: Time and frequency causality analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 480-495.
    7. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek, 2020. "Multiscale characteristics of the emerging global cryptocurrency market," Papers 2010.15403, arXiv.org, revised Mar 2021.
    8. Adarsh Sankaran & Sagar Rohidas Chavan & Mumtaz Ali & Archana Devarajan Sindhu & Drisya Sasi Dharan & Muhammad Ismail Khan, 2021. "Spatiotemporal variability of multifractal properties of fineresolution daily gridded rainfall fields over India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 106(3), pages 1951-1979, April.

  11. Yumei Hou & Qiang Zhang, 2009. "The Optimal Inventory Control Of A System With Random Lead Time Where Random Supply Interruptions Affect The Replenishment," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 26(04), pages 533-557.

    Cited by:

    1. Qing Zhang & Weiguo Fan & Jianchang Lu & Siqian Wu & Xuechao Wang, 2021. "Research on Dynamic Analysis and Mitigation Strategies of Supply Chains under Different Disruption Risks," Sustainability, MDPI, vol. 13(5), pages 1-29, February.

  12. Qiang Zhang & Xiaopeng Wei & Jin Xu, 2007. "On Global Exponential Stability of Discrete-Time Hopfield Neural Networks with Variable Delays," Discrete Dynamics in Nature and Society, Hindawi, vol. 2007, pages 1-9, April.

    Cited by:

    1. Suntonsinsoungvon, E. & Udpin, S., 2020. "Exponential stability of discrete-time uncertain neural networks with multiple time-varying leakage delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 171(C), pages 233-245.

  13. R. H. Liu & Q. Zhang & G. Yin, 2006. "Option pricing in a regime-switching model using the fast Fourier transform," International Journal of Stochastic Analysis, Hindawi, vol. 2006, pages 1-22, September.

    Cited by:

    1. Godin, Frédéric & Trottier, Denis-Alexandre, 2021. "Option pricing in regime-switching frameworks with the Extended Girsanov Principle," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 116-129.
    2. Sha Lin & Xin-Jiang He, 2022. "Analytically Pricing European Options under a New Two-Factor Heston Model with Regime Switching," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1069-1085, March.
    3. Alessandro Ramponi, 2011. "Mixture Dynamics and Regime Switching Diffusions with Application to Option Pricing," Methodology and Computing in Applied Probability, Springer, vol. 13(2), pages 349-368, June.
    4. Godin, Frédéric & Lai, Van Son & Trottier, Denis-Alexandre, 2019. "Option pricing under regime-switching models: Novel approaches removing path-dependence," Insurance: Mathematics and Economics, Elsevier, vol. 87(C), pages 130-142.
    5. Emilio Russo, 2020. "A Discrete-Time Approach to Evaluate Path-Dependent Derivatives in a Regime-Switching Risk Model," Risks, MDPI, vol. 8(1), pages 1-22, January.
    6. Michael C. Fu & Bingqing Li & Rongwen Wu & Tianqi Zhang, 2020. "Option Pricing Under a Discrete-Time Markov Switching Stochastic Volatility with Co-Jump Model," Papers 2006.15054, arXiv.org.
    7. Chinonso I. Nwankwo & Weizhong Dai & Ruihua Liu, 2023. "Compact Finite Difference Scheme with Hermite Interpolation for Pricing American Put Options Based on Regime Switching Model," Computational Economics, Springer;Society for Computational Economics, vol. 62(3), pages 817-854, October.
    8. Mengzhe Zhang & Leunglung Chan, 2016. "Saddlepoint approximations to option price in a regime-switching model," Annals of Finance, Springer, vol. 12(1), pages 55-69, February.
    9. Chinonso Nwankwo & Weizhong Dai & Ruihua Liu, 2019. "Compact Finite Difference Scheme with Hermite Interpolation for Pricing American Put Options Based on Regime Switching Model," Papers 1908.04900, arXiv.org, revised Jun 2020.
    10. Chinonso I. Nwankwo & Weizhong Dai, 2024. "Efficient adaptive strategies with fourth-order compact scheme for a fixed-free boundary regime-switching model," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 47(1), pages 43-82, June.
    11. Xin-Jiang He & Song-Ping Zhu, 2019. "Variance And Volatility Swaps Under A Two-Factor Stochastic Volatility Model With Regime Switching," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(04), pages 1-19, June.
    12. Yue Liu & Nicolas Privault, 2017. "Selling At The Ultimate Maximum In A Regime-Switching Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(03), pages 1-27, May.

  14. Zhang, Qiang & Wei, Xiaopeng & Xu, Jin, 2005. "On global exponential stability of nonautonomous delayed neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 26(3), pages 965-970.

    Cited by:

    1. Qiang Zhang & Xiaopeng Wei & Jin Xu, 2007. "On Global Exponential Stability of Discrete-Time Hopfield Neural Networks with Variable Delays," Discrete Dynamics in Nature and Society, Hindawi, vol. 2007, pages 1-9, April.
    2. Zhang, Qiang & Wei, Xiaopeng & Xu, Jin, 2006. "Stability analysis for cellular neural networks with variable delays," Chaos, Solitons & Fractals, Elsevier, vol. 28(2), pages 331-336.
    3. Li, Dong & Yang, Dan & Wang, Hui & Zhang, Xiaohong & Wang, Shilong, 2009. "Asymptotical stability of multi-delayed cellular neural networks with impulsive effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(2), pages 218-224.
    4. Zhang, Qiang & Wei, Xiaopeng & Xu, Jin, 2009. "Global exponential stability for nonautonomous cellular neural networks with unbounded delays," Chaos, Solitons & Fractals, Elsevier, vol. 39(3), pages 1144-1151.
    5. Zhang, Qiang & Wei, Xiaopeng & Xu, Jin, 2009. "Exponential stability for nonautonomous neural networks with variable delays," Chaos, Solitons & Fractals, Elsevier, vol. 39(3), pages 1152-1157.
    6. Lien, Chang-Hua & Yu, Ker-Wei & Lin, Yen-Feng & Chung, Yeong-Jay & Chung, Long-Yeu, 2009. "Exponential convergence rate estimation for uncertain delayed neural networks of neutral type," Chaos, Solitons & Fractals, Elsevier, vol. 40(5), pages 2491-2499.
    7. Zhang, Qiang & Wei, Xiaopeng & Xu, Jin, 2008. "Delay-dependent exponential stability criteria for non-autonomous cellular neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 36(4), pages 985-990.
    8. Li, Yongkun & Xing, Zhiwei, 2007. "Existence and global exponential stability of periodic solution of CNNs with impulses," Chaos, Solitons & Fractals, Elsevier, vol. 33(5), pages 1686-1693.
    9. Lien, Chang-Hua & Chung, Long-Yeu, 2007. "Global asymptotic stability for cellular neural networks with discrete and distributed time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 34(4), pages 1213-1219.
    10. Zhang, Qiang & Xu, Xiaopeng Wei Jin, 2007. "Delay-dependent global stability results for delayed Hopfield neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 34(2), pages 662-668.
    11. Yu, Ker-Wei & Lien, Chang-Hua, 2008. "Global exponential stability conditions for generalized state-space systems with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 36(4), pages 920-927.
    12. Gau, R.S. & Lien, C.H. & Hsieh, J.G., 2007. "Global exponential stability for uncertain cellular neural networks with multiple time-varying delays via LMI approach," Chaos, Solitons & Fractals, Elsevier, vol. 32(4), pages 1258-1267.

  15. He, Kebin & Huo, Hong & Zhang, Qiang & He, Dongquan & An, Feng & Wang, Michael & Walsh, Michael P., 2005. "Oil consumption and CO2 emissions in China's road transport: current status, future trends, and policy implications," Energy Policy, Elsevier, vol. 33(12), pages 1499-1507, August.

    Cited by:

    1. Sierra, Jaime Cevallos, 2016. "Estimating road transport fuel consumption in Ecuador," Energy Policy, Elsevier, vol. 92(C), pages 359-368.
    2. Yan, Jiaze & Wang, Ge & Chen, Siyuan & Zhang, He & Qian, Jiaqi & Mao, Yuxuan, 2022. "Harnessing freight platforms to promote the penetration of long-haul heavy-duty hydrogen fuel-cell trucks," Energy, Elsevier, vol. 254(PA).
    3. Tehreem Fatima & Enjun Xia & Muhammad Ahad, 2019. "Oil demand forecasting for China: a fresh evidence from structural time series analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(3), pages 1205-1224, June.
    4. Kartal, Mustafa Tevfik, 2022. "The role of consumption of energy, fossil sources, nuclear energy, and renewable energy on environmental degradation in top-five carbon producing countries," Renewable Energy, Elsevier, vol. 184(C), pages 871-880.
    5. Jianlei Lang & Shuiyuan Cheng & Ying Zhou & Beibei Zhao & Haiyan Wang & Shujing Zhang, 2013. "Energy and Environmental Implications of Hybrid and Electric Vehicles in China," Energies, MDPI, vol. 6(5), pages 1-23, May.
    6. Liu, Yang & Wang, Yu & Huo, Hong, 2013. "Temporal and spatial variations in on-road energy use and CO2 emissions in China, 1978–2008," Energy Policy, Elsevier, vol. 61(C), pages 544-550.
    7. Rui Wang, 2011. "Environmental and resource sustainability of Chinese cities: A review of issues, policies, practices and effects," Natural Resources Forum, Blackwell Publishing, vol. 35(2), pages 112-121, May.
    8. Huo, Hong & Zhang, Qiang & He, Kebin & Yao, Zhiliang & Wang, Michael, 2012. "Vehicle-use intensity in China: Current status and future trend," Energy Policy, Elsevier, vol. 43(C), pages 6-16.
    9. Zhou Yuan & Richard S.J. Tol, 2005. "Valuing the health impacts from particulate air pollution in Tianjin," Working Papers FNU-89, Research unit Sustainability and Global Change, Hamburg University, revised Sep 2005.
    10. Talbi, Besma, 2017. "CO2 emissions reduction in road transport sector in Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 232-238.
    11. Chai, Jian & Yang, Ying & Wang, Shouyang & Lai, Kin Keung, 2016. "Fuel efficiency and emission in China's road transport sector: Induced effect and rebound effect," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 188-197.
    12. Hao, Han & Wang, Hewu & Ouyang, Minggao, 2011. "Comparison of policies on vehicle ownership and use between Beijing and Shanghai and their impacts on fuel consumption by passenger vehicles," Energy Policy, Elsevier, vol. 39(2), pages 1016-1021, February.
    13. Huo, Hong & Wang, Michael, 2012. "Modeling future vehicle sales and stock in China," Energy Policy, Elsevier, vol. 43(C), pages 17-29.
    14. Bi, Jun & Zhang, Rongrong & Wang, Haikun & Liu, Miaomiao & Wu, Yi, 2011. "The benchmarks of carbon emissions and policy implications for China's cities: Case of Nanjing," Energy Policy, Elsevier, vol. 39(9), pages 4785-4794, September.
    15. Yang, Jun & Liu, Ying & Qin, Ping & Liu, Antung A., "undated". "A Review of Beijing’s Vehicle Lottery: Short-Term Effects on Vehicle Growth, Congestion, and Fuel Consumption Abstract: Many cities worldwide have considered vehicle restriction policies to curb pro," RFF Working Paper Series dp-14-01-efd, Resources for the Future.
    16. Huo, Hong & Yao, Zhiliang & He, Kebin & Yu, Xin, 2011. "Fuel consumption rates of passenger cars in China: Labels versus real-world," Energy Policy, Elsevier, vol. 39(11), pages 7130-7135.
    17. Dayong Wu & Changwei Yuan & Hongchao Liu, 2018. "The decoupling states of CO2 emissions in the Chinese transport sector from 1994 to 2012: A perspective on fuel types," Energy & Environment, , vol. 29(4), pages 591-612, June.
    18. Cai, Bofeng & Yang, Weishan & Cao, Dong & Liu, Lancui & Zhou, Ying & Zhang, Zhansheng, 2012. "Estimates of China's national and regional transport sector CO2 emissions in 2007," Energy Policy, Elsevier, vol. 41(C), pages 474-483.
    19. Emami Javanmard, M. & Tang, Y. & Wang, Z. & Tontiwachwuthikul, P., 2023. "Forecast energy demand, CO2 emissions and energy resource impacts for the transportation sector," Applied Energy, Elsevier, vol. 338(C).
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    Cited by:

    1. Barış Tan, 2019. "Production Control with Price, Cost, and Demand Uncertainty," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(4), pages 1057-1085, December.
    2. D. Beyer & S. P. Sethi, 1997. "Average Cost Optimality in Inventory Models with Markovian Demands," Journal of Optimization Theory and Applications, Springer, vol. 92(3), pages 497-526, March.
    3. Amir Ahmadi-Javid & Roland Malhamé, 2015. "Optimal Control of a Multistate Failure-Prone Manufacturing System under a Conditional Value-at-Risk Cost Criterion," Journal of Optimization Theory and Applications, Springer, vol. 167(2), pages 716-732, November.
    4. Amir Ahmadi-Javid & Mohsen Ebadi, 2021. "Economic design of memory-type control charts: The fallacy of the formula proposed by Lorenzen and Vance (1986)," Computational Statistics, Springer, vol. 36(1), pages 661-690, March.

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