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Volumn 3498, Issue III, 2005, Pages 634-639

Next day load forecasting using SVM

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SOFTWARE; ELECTRIC LOADS; ERROR ANALYSIS; VECTORS;

EID: 24944514877     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/11427469_101     Document Type: Conference Paper
Times cited : (22)

References (10)
  • 1
    • 0025519319 scopus 로고
    • A regression-based approach to short-term load forecasting
    • Papalexopoulos, A.D., Hesterberg, T.C.: A Regression-based Approach to Short-Term Load Forecasting. IEEE Trans. Power Syst, 5 (1990) 1535-1550
    • (1990) IEEE Trans. Power Syst , vol.5 , pp. 1535-1550
    • Papalexopoulos, A.D.1    Hesterberg, T.C.2
  • 2
    • 0028546825 scopus 로고
    • Regression based peak load forecasting using a transformation technique
    • Haida, T., Muto, S.: Regression Based Peak Load Forecasting Using a Transformation Technique. IEEE Trans. Power Syst., 9 (1994) 1788-1794
    • (1994) IEEE Trans. Power Syst. , vol.9 , pp. 1788-1794
    • Haida, T.1    Muto, S.2
  • 3
    • 0027590291 scopus 로고
    • A generalized knowledge-based short term load-forecasting technique
    • Rahman, S., Hazim, O.,: A Generalized Knowledge-based Short Term Load-forecasting Technique. IEEE Trans. Power Syst, 8 (1993) 508-514
    • (1993) IEEE Trans. Power Syst , vol.8 , pp. 508-514
    • Rahman, S.1    Hazim, O.2
  • 4
    • 0036577946 scopus 로고    scopus 로고
    • A data mining approach for special modeling in small area load forecast
    • Wu, H., Lu, C.: A Data Mining Approach for Special Modeling in Small Area Load Forecast. IEEE Trans. Power Syst, 17 (2003) 516-521
    • (2003) IEEE Trans. Power Syst , vol.17 , pp. 516-521
    • Wu, H.1    Lu, C.2
  • 5
    • 84887252594 scopus 로고    scopus 로고
    • Support vector machine for function approximation, regression estimation and signal procession
    • Vapnik, V.N., Golowich, S.E., Smola, A.J.: Support Vector Machine for Function Approximation, Regression Estimation and Signal Procession. Adv. Neural Information Procession Syst, 9 (1996) 281-287
    • (1996) Adv. Neural Information Procession Syst , vol.9 , pp. 281-287
    • Vapnik, V.N.1    Golowich, S.E.2    Smola, A.J.3
  • 6
    • 0036552848 scopus 로고    scopus 로고
    • A support vector machine approach for short term load forecasting
    • Zhao, D.F., Wang, M.: A Support Vector Machine Approach for Short Term Load Forecasting. Proceedings of the CSEE, 17 (2002) 26-30
    • (2002) Proceedings of the CSEE , vol.17 , pp. 26-30
    • Zhao, D.F.1    Wang, M.2
  • 7
    • 24944463776 scopus 로고    scopus 로고
    • Application of SVM to power system short term load forecasting
    • Yang, J.F, Cheng, H.Z.: Application of SVM to Power System Short Term Load Forecasting. Electric Power Automation Equipment, 24 (2004) 30-32
    • (2004) Electric Power Automation Equipment , vol.24 , pp. 30-32
    • Yang, J.F.1    Cheng, H.Z.2
  • 10
    • 1642634037 scopus 로고    scopus 로고
    • An improved sequential minimal optimization learning algorithm for regression support vector machine
    • Zhang, H.R., Han, Z.Z.: An Improved Sequential Minimal Optimization Learning Algorithm for Regression Support Vector Machine. Journal of Software, 14 (2003) 2006-2013.
    • (2003) Journal of Software , vol.14 , pp. 2006-2013
    • Zhang, H.R.1    Han, Z.Z.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.