Nothing Special   »   [go: up one dir, main page]
create a website
Impact of technological progress on Chinas textile industry and future energy saving potential forecast. (2018). Lin, Boqiang ; Zhang, Guoliang ; Chen, YU.
In: Energy.
RePEc:eee:energy:v:161:y:2018:i:c:p:859-869.

Full description at Econpapers || Download paper

Cited: 14

Citations received by this document

Cites: 71

References cited by this document

Cocites: 50

Documents which have cited the same bibliography

Coauthors: 0

Authors who have wrote about the same topic

Citations

Citations received by this document

  1. Towards sustainable development goals: Does common prosperity contradict carbon reduction?. (2023). Dong, Kangyin ; Taghizadeh-Hesary, Farhad ; Wang, Jianda ; Liu, Yang.
    In: Economic Analysis and Policy.
    RePEc:eee:ecanpo:v:79:y:2023:i:c:p:70-88.

    Full description at Econpapers || Download paper

  2. The Impact of Industrial Intelligence on Energy Intensity: Evidence from China. (2022). Zhu, Hongfei ; Liu, Peiyao ; Zhang, Xiekui.
    In: Sustainability.
    RePEc:gam:jsusta:v:14:y:2022:i:12:p:7219-:d:837522.

    Full description at Econpapers || Download paper

  3. Platform-based servitization and business model adaptation by established manufacturers. (2022). Shen, Lei ; Matthyssens, Paul ; Coreynen, Wim ; Tian, Jiamian.
    In: Technovation.
    RePEc:eee:techno:v:118:y:2022:i:c:s0166497221000031.

    Full description at Econpapers || Download paper

  4. Artificial Intelligence and Energy Intensity in China’s Industrial Sector: Effect and Transmission Channel. (2021). Fujii, Hidemichi ; Liu, Jun ; Yang, Kun.
    In: MPRA Paper.
    RePEc:pra:mprapa:106333.

    Full description at Econpapers || Download paper

  5. How does infrastructure affect energy services?. (2021). Lin, Boqiang ; Chen, YU.
    In: Energy.
    RePEc:eee:energy:v:231:y:2021:i:c:s0360544221013372.

    Full description at Econpapers || Download paper

  6. Supply chain integrated decision model in order to synergize the energy system of textile industry from its resource waste. (2021). Techato, Kuaanan ; Hsieh, Lin-Han Chiang ; Abbas, Shahbaz.
    In: Energy.
    RePEc:eee:energy:v:229:y:2021:i:c:s0360544221010021.

    Full description at Econpapers || Download paper

  7. Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel. (2021). Liu, Jun ; Fujii, Hidemichi ; Yang, Kun.
    In: Economic Analysis and Policy.
    RePEc:eee:ecanpo:v:70:y:2021:i:c:p:276-293.

    Full description at Econpapers || Download paper

  8. Dynamic energy performance evaluation of Chinese textile industry. (2020). Lin, Boqiang ; Bai, Rui.
    In: Energy.
    RePEc:eee:energy:v:199:y:2020:i:c:s0360544220304953.

    Full description at Econpapers || Download paper

  9. Does better access to credit help reduce energy intensity in China? Evidence from manufacturing firms. (2020). Zhang, Dayong ; Ji, Qiang ; Li, Jun.
    In: Energy Policy.
    RePEc:eee:enepol:v:145:y:2020:i:c:s0301421520304377.

    Full description at Econpapers || Download paper

  10. Intellectual Capital Performance of the Textile Industry in Emerging Markets: A Comparison with China and South Korea. (2019). Wang, Binghan ; Xu, Jian.
    In: Sustainability.
    RePEc:gam:jsusta:v:11:y:2019:i:8:p:2354-:d:224305.

    Full description at Econpapers || Download paper

  11. Technological Innovation in Biomass Energy for the Sustainable Growth of Textile Industry. (2019). de Oliveira, Joo Carlos ; Godina, Radu ; Ribeiro, Leonel Jorge.
    In: Sustainability.
    RePEc:gam:jsusta:v:11:y:2019:i:2:p:528-:d:199281.

    Full description at Econpapers || Download paper

  12. Drivers and Barriers to Industrial Energy Efficiency in Textile Industries of Bangladesh. (2019). Tuhin, Rashedul Amin ; Rokonuzzaman, Mohammad ; A S M Monjurul Hasan, ; Thollander, Patrik ; Sakib, Taiyeb Hasan ; Ullah, Mahfuz.
    In: Energies.
    RePEc:gam:jeners:v:12:y:2019:i:9:p:1775-:d:229955.

    Full description at Econpapers || Download paper

  13. Will economic infrastructure development affect the energy intensity of Chinas manufacturing industry?. (2019). Lin, Boqiang ; Chen, YU.
    In: Energy Policy.
    RePEc:eee:enepol:v:132:y:2019:i:c:p:122-131.

    Full description at Econpapers || Download paper

  14. Energy use and energy efficiency development in the German and Colombian textile industries. (2009). Pardo Martinez, Clara ; Clara Ines Pardo Martinez, .
    In: Serie de Documentos en Economía y Violencia.
    RePEc:col:000137:006862.

    Full description at Econpapers || Download paper

References

References cited by this document

  1. An, N. ; Zhao, W. ; Wang, J. Using multi-output feedforward neural network with empirical mode decomposition based signal filtering for electricity demand forecasting. 2013 Energy. 49 279-288

  2. Belloumi, M. Energy consumption and GDP in Tunisia: cointegration and causality analysis. 2009 Energy Pol. 37 2745-2753

  3. Cai, B. ; Zhang, B. ; Bi, J. Energy's thirst for water in China. 2014 Environ Sci Technol. 48 11760-11768
    Paper not yet in RePEc: Add citation now

  4. Chang, K. ; Pei, P. ; Zhang, C. Exploring the price dynamics of CO2 emissions allowances in China's emissions trading scheme pilots. 2017 Energy Econ. 67 213-223

  5. Chen, S. Reconstruction of sub-industrial statistical data in China (1980–2008). 2011 China Econ Q. 10 735-776
    Paper not yet in RePEc: Add citation now
  6. China Energy Statistics Yearbook, N.B.o.S. People's republic of China. 1991-2016 Department of Energy Statistics, China Statistics Press:
    Paper not yet in RePEc: Add citation now
  7. China Industrial Statistical Yearbook, N.B.o.S. . 1991-2016 En : People's republic of China. China Statistics Press: Beijing
    Paper not yet in RePEc: Add citation now
  8. China Statistical Yearbook, N.B.o.S. People's republic of China. 1991-2016 China Statistics Press: Beijing
    Paper not yet in RePEc: Add citation now
  9. Dickey, D.A. ; Fuller, W.A. Distribution of the estimators for autoregressive time series with a unit root. 1979 J Am Stat Assoc. 74 427-431
    Paper not yet in RePEc: Add citation now

  10. Elliott, G. ; Rothenberg, T.J. ; Stock, J.H. Efficient tests for an autoregressive unit root. 1996 Econometrica. 64 813-836

  11. Energy demand in China, Comparison of characteristics between the US and China in rapid urbanization stage. 2014 Energy Convers Manag. 79 128-139
    Paper not yet in RePEc: Add citation now

  12. Engle, R.F. ; Granger, C.W.J. Co-integration and error correction: representation, estimation, and testing. 1987 Econ: J Econ Soc. 251-276

  13. Feng, C. ; Wang, M. The economy-wide energy efficiency in China's regional building industry. 2017 Energy. 141 1869-1879

  14. Guo, Q. ; Jia, J. Estimating total factor productivity in China. 2005 Econ Res J. 6 51-60
    Paper not yet in RePEc: Add citation now

  15. Hamzacebi, C. ; Es, H.A. Forecasting the annual electricity consumption of Turkey using an optimized grey model. 2014 Energy. 70 165-171

  16. Hang, L. ; Tu, M. The impacts of energy prices on energy intensity: evidence from China. 2007 Energy Pol. 35 2978-2988

  17. Hartono, D. ; Irawan, T. ; Achsani, N.A. An analysis of energy intensity in Indonesian manufacturing. 2011 Int Res J Finance Econ. 62 77-84
    Paper not yet in RePEc: Add citation now

  18. Hasanbeigi, A. ; Price, L. A review of energy use and energy efficiency technologies for the textile industry. 2012 Renew Sustain Energy Rev. 16 3648-3665

  19. Hasanbeigi, A. ; Price, L. ; Lu, H. Analysis of energy-efficiency opportunities for the cement industry in Shandong Province, China: a case study of 16 cement plants. 2010 Energy. 35 3461-3473

  20. He, X. ; Wang, Z. Energy biased technology progress and green growth transformation—an empirical analysis based on 33 industries of China. 2015 China Industrial Economics:
    Paper not yet in RePEc: Add citation now

  21. Hendry, D.F. ; Juselius, K. Explaining cointegration analysis: Part II. 2001 Energy J. 75-120

  22. Hondroyiannis, G. Estimating residential demand for electricity in Greece. 2004 Energy Econ. 26 319-334

  23. Hong, G.B. ; Su, T.L. ; Lee, J.D. Energy conservation potential in Taiwanese textile industry. 2010 Energy Pol. 38 7048-7053

  24. Hu, J.L. ; Kao, C.H. Efficient energy-saving targets for APEC economies. 2007 Energy Pol. 35 373-382

  25. Johansen, S. ; Juselius, K. Maximum likelihood estimation and inference on cointegration—with applications to the demand for money. 1990 Oxf Bull Econ Stat. 52 169-210

  26. Kaytez, F. ; Taplamacioglu, M.C. ; Cam, E. Forecasting electricity consumption: a comparison of regression analysis, neural networks and least squares support vector machines. 2015 Int J Electr Power Energy Syst. 67 431-438
    Paper not yet in RePEc: Add citation now

  27. Kitamura, Y. Likelihood-based inference in cointegrated vector autoregressive models. 1998 Econom Theor. 14 517-524

  28. Lin, B. ; Du, K. Technology gap and China's regional energy efficiency: a parametric metafrontier approach. 2013 Energy Econ. 40 529-536

  29. Lin, B. ; Jia, Z. Impact of quota decline scheme of emission trading in China: a dynamic recursive CGE model. 2018 Energy. 149 190-203

  30. Lin, B. ; Jia, Z. The impact of Emission Trading Scheme (ETS) and the choice of coverage industry in ETS: a case study in China. 2017 Appl Energy. 205 1512-1527

  31. Lin, B. ; Liu, H. Do energy and environment efficiency benefit from foreign Trade? —The case of China's industrial sectors. 2015 Econ Res J. 9 127-141
    Paper not yet in RePEc: Add citation now

  32. Lin, B. ; Moubarak, M. Estimation of energy saving potential in China's paper industry. 2014 Energy. 65 182-189

  33. Lin, B. ; Moubarak, M. Mitigation potential of carbon dioxide emissions in the Chinese textile industry. 2014 Appl Energy. 113 781-787

  34. Lin, B. ; Moubarak, M. ; Ouyang, X. Carbon dioxide emissions and growth of the manufacturing sector: evidence for China. 2014 Energy. 76 830-837

  35. Lin, B. ; Tan, R. China's CO2 emissions of a critical sector: evidence from energy intensive industries. 2017 J Clean Prod. 142 4270-4281
    Paper not yet in RePEc: Add citation now
  36. Lin, B. ; Tan, R. Estimating energy conservation potential in China's energy intensive industries with rebound effect. 2017 J Clean Prod. 156 899-910
    Paper not yet in RePEc: Add citation now

  37. Lin, B. ; Wang, X. Exploring energy efficiency in China׳ s iron and steel industry: a stochastic frontier approach. 2014 Energy Pol. 72 87-96

  38. Lin, B. ; Wang, X. Promoting energy conservation in China's iron & steel sector. 2014 Energy. 73 465-474

  39. Lin, B. ; Xie, C. Estimation on oil demand and oil saving potential of China's road transport sector. 2013 Energy Pol. 61 472-482

  40. Lin, B. ; Zhang, G. Estimates of electricity saving potential in Chinese nonferrous metals industry. 2013 Energy Pol. 60 558-568

  41. Lin, B. ; Zhang, L. ; Wu, Y. Evaluation of electricity saving potential in China's chemical industry based on cointegration. 2012 Energy Pol. 44 320-330

  42. Lin, B. ; Zhao, H. Technological progress and energy rebound effect in China׳ s textile industry: evidence and policy implications. 2016 Renew Sustain Energy Rev. 60 173-181

  43. Lin, B. ; Zhao, H. Technology gap and regional energy efficiency in China's textile industry: a non-parametric meta-frontier approach. 2016 J Clean Prod. 137 21-28
    Paper not yet in RePEc: Add citation now
  44. Lin, B.Q. Electricity demand in the People's Republic of China: investment requirement and environmental impact. 2003 Asian Development Bank:
    Paper not yet in RePEc: Add citation now

  45. Liu, Y. Exploring the relationship between urbanization and energy consumption in China using ARDL (autoregressive distributed lag) and FDM (factor decomposition model). 2009 Energy. 34 1846-1854

  46. Ltkepohl, H. . 2005 Springer:
    Paper not yet in RePEc: Add citation now
  47. Martínez, C.I.P. Energy use and energy efficiency development in the German and Colombian textile industries. 2010 Energy Sustain Dev. 14 94-103
    Paper not yet in RePEc: Add citation now

  48. Meier, A. ; Rosenfeld, A.H. ; Wright, J. Supply curves of conserved energy for California's residential sector. 1982 Energy. 7 347-358

  49. Metropolis, N. ; Ulam, S. The Monte Carlo method. 1949 J Am Stat Assoc. 44 335-341
    Paper not yet in RePEc: Add citation now

  50. Mukherjee, K. Energy use efficiency in the Indian manufacturing sector: an interstate analysis. 2008 Energy Pol. 36 662-672

  51. Nabavi-Pelesaraei, A. ; Hosseinzadeh-Bandbafha, H. ; Qasemi-Kordkheili, P. Applying optimization techniques to improve of energy efficiency and GHG (greenhouse gas) emissions of wheat production. 2016 Energy. 103 672-678

  52. Osterwald-Lenum, M. A note with quantiles of the asymptotic distribution of the maximum likelihood cointegration rank test statistics. 1992 Oxf Bull Econ Stat. 54 461-472

  53. Palanichamy, C. ; Babu, N.S. Second stage energy conservation experience with a textile industry. 2005 Energy Pol. 33 603-609

  54. Peng, L. ; Zhang, Y. ; Wang, Y. Energy efficiency and influencing factor analysis in the overall Chinese textile industry. 2015 Energy. 93 1222-1229

  55. Phillips, P.C.B. ; Hansen, B.E. Statistical inference in instrumental variables regression with I (1) processes. 1990 Rev Econ Stud. 57 99-125

  56. Phillips, P.C.B. ; Perron, P. Testing for a unit root in time series regression. 1988 Biometrika. 75 335-346
    Paper not yet in RePEc: Add citation now

  57. Saikkonen, P. Asymptotically efficient estimation of cointegration regressions. 1991 Econom Theor. 7 1-21

  58. Song, M.L. ; Zhang, L.L. ; Liu, W. Bootstrap-DEA analysis of BRICS’energy efficiency based on small sample data. 2013 Appl Energy. 112 1049-1055

  59. Tang, C. ; Tan, E. Exploring the nexus of electricity consumption, economic growth, energy prices and technology innovation in Malaysia. 2013 Appl Energy. 104 297-305

  60. Uri, N.D. ; Flanagan, S.P. Short-term forecasting of crude petroleum and natural gas production. 1979 Appl Energy. 5 297-310

  61. Wang, L. ; Mathew, P. ; Pang, X. Uncertainties in energy consumption introduced by building operations and weather for a medium-size office building. 2012 Energy Build. 53 152-158
    Paper not yet in RePEc: Add citation now
  62. Wang, Y. ; Lin, H. ; Chen, L. The effect of global value chain embeddedness on technical progress—an empirical study on panel data of China's industries. 2014 China Ind Econ. 9 65-77
    Paper not yet in RePEc: Add citation now

  63. Welsch, H. ; Ochsen, C. The determinants of aggregate energy use in West Germany: factor substitution, technological change, and trade. 2005 Energy Econ. 27 93-111

  64. Wolde-Rufael, Y. Bounds test approach to cointegration and causality between nuclear energy consumption and economic growth in India. 2010 Energy Pol. 38 52-58

  65. Worrell, E. ; Martin, N. ; Price, L. Potentials for energy efficiency improvement in the US cement industry. 2000 Energy. 25 1189-1214

  66. Xie, N. ; Yuan, C. ; Yang, Y. Forecasting China's energy demand and self-sufficiency rate by grey forecasting model and Markov model. 2015 Int J Electr Power Energy Syst. 66 1-8
    Paper not yet in RePEc: Add citation now
  67. Yuan, C. ; Liu, S. ; Wu, J. Research on energy-saving effect of technological progress based on Cobb–Douglas production function. 2009 Energy Pol. 37 2842-2846
    Paper not yet in RePEc: Add citation now

  68. Yuan, C. ; Liu, S. ; Wu, J. Research on energy-saving effect of technological progress based on Cobb–Douglas production function. 2009 Energy Pol. 37 2842-2846

  69. Zhang, B. ; Yang, S. ; Bi, J. Enterprises' willingness to adopt/develop cleaner production technologies: an empirical study in Changshu, China. 2013 J Clean Prod. 40 62-70
    Paper not yet in RePEc: Add citation now

  70. Zhou, P. ; Ang, B.W. Decomposition of aggregate CO2 emissions: a production-theoretical approach. 2008 Energy Econ. 30 1054-1067

  71. Zhu, L. ; Chen, L. ; Wu, X. Developing a greenhouse gas manlagement evaluation system for Chinese textile enterprises. 2018 Ecol Indicat. 91 470-477
    Paper not yet in RePEc: Add citation now

Cocites

Documents in RePEc which have cited the same bibliography

  1. Prediction of electricity consumption based on GM(1,Nr) model in Jiangsu province, China. (2023). Yan, Yabo ; Wu, Dongdong ; Du, Xiaoyi.
    In: Energy.
    RePEc:eee:energy:v:262:y:2023:i:pa:s0360544222023210.

    Full description at Econpapers || Download paper

  2. Multistage optimization filter for trend?based short?term forecasting. (2022). Vinogradov, Dmitri ; Kellard, Neil ; Zafar, Usman.
    In: Journal of Forecasting.
    RePEc:wly:jforec:v:41:y:2022:i:2:p:345-360.

    Full description at Econpapers || Download paper

  3. Ultra-Short-Term Wind Speed Forecasting Using the Hybrid Model of Subseries Reconstruction and Broad Learning System. (2022). Zhang, Yajun ; Pang, Ming ; Deng, Zhepeng ; Dou, Jianming ; Zhou, AO.
    In: Energies.
    RePEc:gam:jeners:v:15:y:2022:i:12:p:4492-:d:843317.

    Full description at Econpapers || Download paper

  4. Dataset level explanation of heat demand forecasting ANN with SHAP. (2022). Wojdan, Konrad ; Bujalski, Wojciech ; Biaek, Jakub ; Kurek, Teresa ; Guzek, Micha.
    In: Energy.
    RePEc:eee:energy:v:261:y:2022:i:pa:s0360544222019703.

    Full description at Econpapers || Download paper

  5. Forecasting Chinas energy production and consumption based on a novel structural adaptive Caputo fractional grey prediction model. (2022). Ma, Xin ; Wang, LI ; Yang, Zhongsen ; Luo, Yongxian ; Zhou, Ying ; Ye, Lingling ; Wu, Wenqing.
    In: Energy.
    RePEc:eee:energy:v:259:y:2022:i:c:s0360544222018369.

    Full description at Econpapers || Download paper

  6. An adaptive hybrid ensemble with pattern similarity analysis and error correction for short-term load forecasting. (2022). Boukelia, Taqiy eddine ; Laouafi, Farida.
    In: Applied Energy.
    RePEc:eee:appene:v:322:y:2022:i:c:s0306261922008431.

    Full description at Econpapers || Download paper

  7. Advanced statistical learning on short term load process forecasting. (2021). Hu, Junjie ; Melzer, Awdesch ; Cabrera, Brenda Lopez.
    In: IRTG 1792 Discussion Papers.
    RePEc:zbw:irtgdp:2021020.

    Full description at Econpapers || Download paper

  8. Machine learning for occupant-behavior-sensitive cooling energy consumption prediction in office buildings. (2021). El-Gohary, Nora ; Amasyali, Kadir.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:142:y:2021:i:c:s1364032121000113.

    Full description at Econpapers || Download paper

  9. A novel hybrid machine learning model for short-term wind speed prediction in inner Mongolia, China. (2021). Lin, Boqiang ; Zhang, Chongchong.
    In: Renewable Energy.
    RePEc:eee:renene:v:179:y:2021:i:c:p:1565-1577.

    Full description at Econpapers || Download paper

  10. A multivariate grey prediction model based on energy logistic equation and its application in energy prediction in China. (2021). Pang, Xinyu ; Duan, Huiming.
    In: Energy.
    RePEc:eee:energy:v:229:y:2021:i:c:s0360544221009646.

    Full description at Econpapers || Download paper

  11. Medium, short and very short-term prognosis of load demand for the Greek Island of Tilos using artificial neural networks and human thermal comfort-discomfort biometeorological data. (2020). Moustris, K ; Kaldellis, J K ; Zafirakis, D ; Kavadias, K A.
    In: Renewable Energy.
    RePEc:eee:renene:v:147:y:2020:i:p1:p:100-109.

    Full description at Econpapers || Download paper

  12. Forecasting the industrial solar energy consumption using a novel seasonal GM(1,1) model with dynamic seasonal adjustment factors. (2020). Li, Qin ; Wang, Zhi-Wei.
    In: Energy.
    RePEc:eee:energy:v:200:y:2020:i:c:s0360544220305673.

    Full description at Econpapers || Download paper

  13. A novel composite electricity demand forecasting framework by data processing and optimized support vector machine. (2020). Gao, Yuyang ; Liu, Ningning ; Jiang, Ping.
    In: Applied Energy.
    RePEc:eee:appene:v:260:y:2020:i:c:s0306261919319300.

    Full description at Econpapers || Download paper

  14. Estimating Sleep & Work Hours from Alternative Data by Segmented Functional Classification Analysis (SFCA). (2020). Raschky, Paul ; Ackermann, Klaus ; Angus, Simon D.
    In: Papers.
    RePEc:arx:papers:2010.08102.

    Full description at Econpapers || Download paper

  15. .

    Full description at Econpapers || Download paper

  16. A Novel Optimized Nonlinear Grey Bernoulli Model for Forecasting China’s GDP. (2019). Zhang, Tao ; Wu, Wen-Ze ; Zheng, Chengli.
    In: Complexity.
    RePEc:hin:complx:1731262.

    Full description at Econpapers || Download paper

  17. Research and Application of a Novel Hybrid Model Based on a Deep Neural Network for Electricity Load Forecasting: A Case Study in Australia. (2019). Tang, Guangyu ; Wang, Jianzhou ; Ni, Kailai ; Wei, Danxiang.
    In: Energies.
    RePEc:gam:jeners:v:12:y:2019:i:13:p:2467-:d:243188.

    Full description at Econpapers || Download paper

  18. Prediction of occupancy level and energy consumption in office building using blind system identification and neural networks. (2019). Li, Qingping ; Xie, Jingchao ; Zhang, Weiya ; Wu, Jinshun ; Pan, Song ; Xia, Liang ; Wei, Yixuan.
    In: Applied Energy.
    RePEc:eee:appene:v:240:y:2019:i:c:p:276-294.

    Full description at Econpapers || Download paper

  19. Degradation Tendency Measurement of Aircraft Engines Based on FEEMD Permutation Entropy and Regularized Extreme Learning Machine Using Multi-Sensor Data. (2018). Shan, Yahui ; Xu, Yanhe ; Jiang, Wei ; Liu, Han.
    In: Energies.
    RePEc:gam:jeners:v:11:y:2018:i:12:p:3301-:d:185625.

    Full description at Econpapers || Download paper

  20. Forecasting methods in energy planning models. (2018). Debnath, Kumar Biswajit ; Mourshed, Monjur.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:88:y:2018:i:c:p:297-325.

    Full description at Econpapers || Download paper

  21. Impact of technological progress on Chinas textile industry and future energy saving potential forecast. (2018). Lin, Boqiang ; Zhang, Guoliang ; Chen, YU.
    In: Energy.
    RePEc:eee:energy:v:161:y:2018:i:c:p:859-869.

    Full description at Econpapers || Download paper

  22. A novel data-driven approach for residential electricity consumption prediction based on ensemble learning. (2018). Chen, Kunlong ; Zheng, Fangdan ; Jiang, Jiuchun.
    In: Energy.
    RePEc:eee:energy:v:150:y:2018:i:c:p:49-60.

    Full description at Econpapers || Download paper

  23. Short-term power output forecasting of hourly operation in power plant based on climate factors and effects of wind direction and wind speed. (2018). Dadkhah, Mojtaba ; Chavoshi, Ahmad Zare ; Rezaee, Mustafa Jahangoshai.
    In: Energy.
    RePEc:eee:energy:v:148:y:2018:i:c:p:775-788.

    Full description at Econpapers || Download paper

  24. Modeling a combined forecast algorithm based on sequence patterns and near characteristics: An application for tourism demand forecasting. (2018). Yuyan, Luo ; Jun, Wang ; Peng, GE ; Lingyu, Tang.
    In: Chaos, Solitons & Fractals.
    RePEc:eee:chsofr:v:108:y:2018:i:c:p:136-147.

    Full description at Econpapers || Download paper

  25. A combination forecasting approach applied in multistep wind speed forecasting based on a data processing strategy and an optimized artificial intelligence algorithm. (2018). Yang, Zhongshan ; Wang, Jian.
    In: Applied Energy.
    RePEc:eee:appene:v:230:y:2018:i:c:p:1108-1125.

    Full description at Econpapers || Download paper

  26. A review of the decomposition methodology for extracting and identifying the fluctuation characteristics in electricity demand forecasting. (2017). Shao, Zhen ; Zhou, Kai-Le ; Yang, Shan-Lin ; Chao, FU.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:75:y:2017:i:c:p:123-136.

    Full description at Econpapers || Download paper

  27. A seasonal direct optimal hybrid model of computational intelligence and soft computing techniques for electricity load forecasting. (2017). Khashei, Mehdi ; Chahkoutahi, Fatemeh.
    In: Energy.
    RePEc:eee:energy:v:140:y:2017:i:p1:p:988-1004.

    Full description at Econpapers || Download paper

  28. Forecasting carbon price using empirical mode decomposition and evolutionary least squares support vector regression. (2017). Wei, Yi-Ming ; Zhang, Tao ; Wu, Zhanchi ; Wang, Ping ; Zhu, Bangzhu.
    In: Applied Energy.
    RePEc:eee:appene:v:191:y:2017:i:c:p:521-530.

    Full description at Econpapers || Download paper

  29. Forecasting Electricity Market Risk Using Empirical Mode Decomposition (EMD)—Based Multiscale Methodology. (2016). Du, Jiangze ; Wang, Hongqian ; He, Kaijian ; Zou, Yingchao.
    In: Energies.
    RePEc:gam:jeners:v:9:y:2016:i:11:p:931-:d:82489.

    Full description at Econpapers || Download paper

  30. Forecasting the natural gas demand in China using a self-adapting intelligent grey model. (2016). Zeng, BO ; Li, Chuan.
    In: Energy.
    RePEc:eee:energy:v:112:y:2016:i:c:p:810-825.

    Full description at Econpapers || Download paper

  31. The long-term trends on the electricity markets: Comparison of empirical mode and wavelet decompositions. (2016). Afanasyev, Dmitriy ; Fedorova, Elena A.
    In: Energy Economics.
    RePEc:eee:eneeco:v:56:y:2016:i:c:p:432-442.

    Full description at Econpapers || Download paper

  32. One day ahead wind speed forecasting: A resampling-based approach. (2016). Zhao, Weigang ; Wei, Yi-Ming ; Su, Zhongyue .
    In: Applied Energy.
    RePEc:eee:appene:v:178:y:2016:i:c:p:886-901.

    Full description at Econpapers || Download paper

  33. The long-term trends on Russian electricity market: comparison of empirical mode and wavelet decompositions. (2015). Afanasyev, Dmitriy ; Fedorova, Elena .
    In: MPRA Paper.
    RePEc:pra:mprapa:62391.

    Full description at Econpapers || Download paper

  34. A new semiparametric and EEMD based framework for mid-term electricity demand forecasting in China: Hidden characteristic extraction and probability density prediction. (2015). Shao, Zhen ; Yu, Ben-Gong ; Yang, Shan-Lin ; Gao, Fei.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:52:y:2015:i:c:p:876-889.

    Full description at Econpapers || Download paper

  35. Electricity price forecasting with a BED (Bivariate EMD Denoising) methodology. (2015). Yu, Lean ; Tang, Ling ; He, Kaijian.
    In: Energy.
    RePEc:eee:energy:v:91:y:2015:i:c:p:601-609.

    Full description at Econpapers || Download paper

  36. The use of a sky camera for solar radiation estimation based on digital image processing. (2015). Alonso-Montesinos, J ; Batlles, F J.
    In: Energy.
    RePEc:eee:energy:v:90:y:2015:i:p1:p:377-386.

    Full description at Econpapers || Download paper

  37. Estimating zonal electricity supply curves in transmission-constrained electricity markets. (2015). Sahraei-Ardakani, Mostafa ; Kleit, Andrew ; Blumsack, Seth .
    In: Energy.
    RePEc:eee:energy:v:80:y:2015:i:c:p:10-19.

    Full description at Econpapers || Download paper

  38. Fine structure of the price–demand relationship in the electricity market: Multi-scale correlation analysis. (2015). Afanasyev, Dmitriy ; Fedorova, Elena A ; Popov, Viktor U.
    In: Energy Economics.
    RePEc:eee:eneeco:v:51:y:2015:i:c:p:215-226.

    Full description at Econpapers || Download paper

  39. A decomposition–ensemble model with data-characteristic-driven reconstruction for crude oil price forecasting. (2015). Yu, Lean ; Tang, Ling ; Wang, Zishu .
    In: Applied Energy.
    RePEc:eee:appene:v:156:y:2015:i:c:p:251-267.

    Full description at Econpapers || Download paper

  40. Fine structure of the price-demand relationship in the electricity market: multi-scale correlation analysis. (2014). Afanasyev, Dmitriy ; Fedorova, Elena ; Popov, Viktor .
    In: MPRA Paper.
    RePEc:pra:mprapa:58827.

    Full description at Econpapers || Download paper

  41. Combining forecasts of electricity consumption in China with time-varying weights updated by a high-order Markov chain model. (2014). Zhao, Weigang ; Lu, Hai Yan ; Wang, Jianzhou.
    In: Omega.
    RePEc:eee:jomega:v:45:y:2014:i:c:p:80-91.

    Full description at Econpapers || Download paper

  42. Artificial neural networks for short-term load forecasting in microgrids environment. (2014). Sanchez-Esguevillas, Antonio ; Hernandez, Luis ; Aguiar, Javier M. ; Lloret, Jaime ; Baladron, Carlos ; Carro, Belen .
    In: Energy.
    RePEc:eee:energy:v:75:y:2014:i:c:p:252-264.

    Full description at Econpapers || Download paper

  43. Uncertainty handling using neural network-based prediction intervals for electrical load forecasting. (2014). Khosravi, Abbas ; Quan, Hao ; Srinivasan, Dipti.
    In: Energy.
    RePEc:eee:energy:v:73:y:2014:i:c:p:916-925.

    Full description at Econpapers || Download paper

  44. Short and medium-term cloudiness forecasting using remote sensing techniques and sky camera imagery. (2014). Batlles, F. J. ; Alonso, J..
    In: Energy.
    RePEc:eee:energy:v:73:y:2014:i:c:p:890-897.

    Full description at Econpapers || Download paper

  45. Forecasting the annual electricity consumption of Turkey using an optimized grey model. (2014). Hamzacebi, Coskun ; Es, Huseyin Avni .
    In: Energy.
    RePEc:eee:energy:v:70:y:2014:i:c:p:165-171.

    Full description at Econpapers || Download paper

  46. Sky camera imagery processing based on a sky classification using radiometric data. (2014). Ternero, A. ; Alonso, J. ; Lopez, G. ; Batlles, F. J..
    In: Energy.
    RePEc:eee:energy:v:68:y:2014:i:c:p:599-608.

    Full description at Econpapers || Download paper

  47. Estimating industrial and residential electricity demand in Turkey: A time varying parameter approach. (2014). Ozturk, Ilhan ; Arisoy, Ibrahim .
    In: Energy.
    RePEc:eee:energy:v:66:y:2014:i:c:p:959-964.

    Full description at Econpapers || Download paper

  48. Modeling solar radiation of Mediterranean region in Turkey by using fuzzy genetic approach. (2014). Kisi, Ozgur.
    In: Energy.
    RePEc:eee:energy:v:64:y:2014:i:c:p:429-436.

    Full description at Econpapers || Download paper

  49. An adaptive load dispatching and forecasting strategy for a virtual power plant including renewable energy conversion units. (2014). Karakas, A. ; Erdinc, O. ; Uzunoglu, M. ; Tascikaraoglu, A..
    In: Applied Energy.
    RePEc:eee:appene:v:119:y:2014:i:c:p:445-453.

    Full description at Econpapers || Download paper

  50. Short-term electric load and temperature forecasting using wavelet echo state networks with neural reconstruction. (2013). Deihimi, Ali ; Orang, Omid ; Showkati, Hemen .
    In: Energy.
    RePEc:eee:energy:v:57:y:2013:i:c:p:382-401.

    Full description at Econpapers || Download paper

Coauthors

Authors registered in RePEc who have wrote about the same topic

Report date: 2024-12-26 10:57:29 || Missing content? Let us know

CitEc is a RePEc service, providing citation data for Economics since 2001. Sponsored by INOMICS. Last updated October, 6 2023. Contact: CitEc Team.