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Volumn 25, Issue 7-8, 2014, Pages 1967-1978

An efficient model based on artificial bee colony optimization algorithm with Neural Networks for electric load forecasting

Author keywords

Artificial bee colony algorithm; Artificial Neural Networks; Genetic algorithm; Optimization techniques; Particle swarm optimization; Short term load forecasting

Indexed keywords

ELECTRIC POWER PLANT LOADS; FORECASTING; GENETIC ALGORITHMS; NEURAL NETWORKS; PARTICLE SWARM OPTIMIZATION (PSO);

EID: 84920252463     PISSN: 09410643     EISSN: 14333058     Source Type: Journal    
DOI: 10.1007/s00521-014-1685-y     Document Type: Article
Times cited : (61)

References (39)
  • 1
    • 84867745784 scopus 로고    scopus 로고
    • A hybrid intelligent algorithm based short-term load forecasting approach
    • Hooshmand Rahmat-Allah, Amooshahi Habib, Parastegari Moein (2013) A hybrid intelligent algorithm based short-term load forecasting approach. Int J Electr Power Energy Syst 45(1):313–324
    • (2013) Int J Electr Power Energy Syst , vol.45 , Issue.1 , pp. 313-324
    • Hooshmand, R.-A.1    Amooshahi, H.2    Parastegari, M.3
  • 2
    • 0036275409 scopus 로고    scopus 로고
    • Electric load forecasting: literature survey and classification of methods
    • Alfares Hesham K, Nazeeruddin Mohammad (2002) Electric load forecasting: literature survey and classification of methods. Int J Syst Sci 33(1):23–34
    • (2002) Int J Syst Sci , vol.33 , Issue.1 , pp. 23-34
    • Alfares, H.K.1    Nazeeruddin, M.2
  • 3
    • 79151485446 scopus 로고    scopus 로고
    • Load forecasting using hybrid models
    • Hanmandlu Madasu, Chauhan Bhavesh Kumar (2011) Load forecasting using hybrid models. IEEE Trans Power Syst 26(1):20–29
    • (2011) IEEE Trans Power Syst , vol.26 , Issue.1 , pp. 20-29
    • Hanmandlu, M.1    Chauhan, B.K.2
  • 4
    • 67349154089 scopus 로고    scopus 로고
    • Electric load forecasting methods: tools for decision making
    • Hahn H, Meyer-Nieberg S, Pickl S (2009) Electric load forecasting methods: tools for decision making. Eur J Oper Res 199(3):902–907
    • (2009) Eur J Oper Res , vol.199 , Issue.3 , pp. 902-907
    • Hahn, H.1    Meyer-Nieberg, S.2    Pickl, S.3
  • 5
    • 84855292182 scopus 로고    scopus 로고
    • Energy models for demand forecasting—a review
    • Suganthi L, Samuel AA (2012) Energy models for demand forecasting—a review. Renew Sustain Energy Rev 16(2):1223–1240
    • (2012) Renew Sustain Energy Rev , vol.16 , Issue.2 , pp. 1223-1240
    • Suganthi, L.1    Samuel, A.A.2
  • 6
    • 84867693003 scopus 로고    scopus 로고
    • Neural-based electricity load forecasting using hybrid of ga and aco for feature selection
    • Sheikhan M, Mohammadi N (2012) Neural-based electricity load forecasting using hybrid of ga and aco for feature selection. Neural Comput Appl 21:1961–1970
    • (2012) Neural Comput Appl , vol.21 , pp. 1961-1970
    • Sheikhan, M.1    Mohammadi, N.2
  • 7
    • 84920252847 scopus 로고
    • Wiley-Interscience, New York, NY, USA:
    • Fletcher R (1987) Pract Methods Optim, 2nd edn. Wiley-Interscience, New York, NY, USA
    • (1987) Pract Methods Optim
    • Fletcher, R.1
  • 8
    • 35148821762 scopus 로고    scopus 로고
    • A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm
    • Karaboga Dervis, Basturk Bahriye (2007) A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. J Glob Optim 39(3):459–471
    • (2007) J Glob Optim , vol.39 , Issue.3 , pp. 459-471
    • Karaboga, D.1    Basturk, B.2
  • 10
    • 0003463297 scopus 로고
    • Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence
    • Holland John H (1992) Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. U Michigan Press
    • (1992) U Michigan Press
    • Holland John, H.1
  • 11
    • 0037505508 scopus 로고    scopus 로고
    • Short-term load forecasting via ARMA model identification including non-gaussian process considerations
    • Huang S-J, Shih K-R (2003) Short-term load forecasting via ARMA model identification including non-gaussian process considerations. IEEE Trans Power Syst 18(2):673–679
    • (2003) IEEE Trans Power Syst , vol.18 , Issue.2 , pp. 673-679
    • Huang, S.-J.1    Shih, K.-R.2
  • 12
    • 84860245764 scopus 로고    scopus 로고
    • Holiday load forecasting using fuzzy polynomial regression with weather feature selection and adjustment
    • Wi Y-M, Joo S-K, Song K-B (2012) Holiday load forecasting using fuzzy polynomial regression with weather feature selection and adjustment. IEEE Trans Power Syst 27(2):596–603
    • (2012) IEEE Trans Power Syst , vol.27 , Issue.2 , pp. 596-603
    • Wi, Y.-M.1    Joo, S.-K.2    Song, K.-B.3
  • 13
    • 84856296455 scopus 로고    scopus 로고
    • Short-term load forecasting with exponentially weighted methods
    • Taylor JW (2012) Short-term load forecasting with exponentially weighted methods. IEEE Trans Power Syst 27(1):458–464
    • (2012) IEEE Trans Power Syst , vol.27 , Issue.1 , pp. 458-464
    • Taylor, J.W.1
  • 14
    • 0032142541 scopus 로고    scopus 로고
    • Nonparametric regression based short-term load forecasting
    • Charytoniuk W, Chen MS, Van Olinda P (1998) Nonparametric regression based short-term load forecasting. IEEE Trans Power Syst 13(3):725–730
    • (1998) IEEE Trans Power Syst , vol.13 , Issue.3 , pp. 725-730
    • Charytoniuk, W.1    Chen, M.S.2    Van Olinda, P.3
  • 15
    • 0033362601 scopus 로고    scopus 로고
    • Evolving artificial neural networks
    • Yao X (1999) Evolving artificial neural networks. IEEE Proc 87(9):1423–1447
    • (1999) IEEE Proc , vol.87 , Issue.9 , pp. 1423-1447
    • Yao, X.1
  • 17
    • 4043137356 scopus 로고    scopus 로고
    • A tutorial on support vector regression
    • Smola AJ, Schölkopf B (2004) A tutorial on support vector regression. Stat Comput 14(3):199–222
    • (2004) Stat Comput , vol.14 , Issue.3 , pp. 199-222
    • Smola, A.J.1    Schölkopf, B.2
  • 21
    • 77958467490 scopus 로고    scopus 로고
    • Application of chaotic ant swarm optimization in electric load forecasting
    • Hong Wei-Chiang (2010) Application of chaotic ant swarm optimization in electric load forecasting. Energy Policy 38(10):5830–5839
    • (2010) Energy Policy , vol.38 , Issue.10 , pp. 5830-5839
    • Hong, W.-C.1
  • 22
    • 84866563098 scopus 로고    scopus 로고
    • Cyclic electric load forecasting by seasonal svr with chaotic genetic algorithm
    • Hong Wei-Chiang, Dong Yucheng (2013) Cyclic electric load forecasting by seasonal svr with chaotic genetic algorithm. Int J Electr Power Energy Syst 44(1):604–614
    • (2013) Int J Electr Power Energy Syst , vol.44 , Issue.1 , pp. 604-614
    • Hong, W.-C.1    Dong, Y.2
  • 23
    • 84862777006 scopus 로고    scopus 로고
    • An annual load forecasting model based on support vector regression with differential evolution algorithm
    • Wang Jianjun, Li Li, Niu Dongxiao, Tan Zhongfu (2012) An annual load forecasting model based on support vector regression with differential evolution algorithm. Appl Energy 94:65–70
    • (2012) Appl Energy , vol.94 , pp. 65-70
    • Wang, J.1    Li, L.2    Niu, D.3    Tan, Z.4
  • 24
    • 84904181323 scopus 로고    scopus 로고
    • Short term electric load forecasting by wavelet transform and grey model improved by PSO (particle swarm optimization) algorithm
    • Bahrami S, Hooshmand R-A, Parastegari M (2014) Short term electric load forecasting by wavelet transform and grey model improved by PSO (particle swarm optimization) algorithm. Energy 72:434–442
    • (2014) Energy , vol.72 , pp. 434-442
    • Bahrami, S.1    Hooshmand, R.-A.2    Parastegari, M.3
  • 25
    • 84891616845 scopus 로고    scopus 로고
    • Hybrid pso-svm method for short-term load forecasting during periods with significant temperature variations in city of burbank
    • Selakov A, Cvijetinović D, Milović L, Mellon S, Bekut D (2014) Hybrid pso-svm method for short-term load forecasting during periods with significant temperature variations in city of burbank. Appl Soft Comput 16:80–88
    • (2014) Appl Soft Comput , vol.16 , pp. 80-88
    • Selakov, A.1    Cvijetinović, D.2    Milović, L.3    Mellon, S.4    Bekut, D.5
  • 27
    • 67349273050 scopus 로고    scopus 로고
    • A comparative study of artificial bee colony algorithm
    • Karaboga D, Akay B (2009) A comparative study of artificial bee colony algorithm. Appl Math Comput 214(1):108–132
    • (2009) Appl Math Comput , vol.214 , Issue.1 , pp. 108-132
    • Karaboga, D.1    Akay, B.2
  • 28
    • 80055056236 scopus 로고    scopus 로고
    • Performance assessment of foraging algorithms vs. evolutionary algorithms
    • El-Abd Mohammed (2012) Performance assessment of foraging algorithms vs. evolutionary algorithms. Inf Sci 182(1):243–263
    • (2012) Inf Sci , vol.182 , Issue.1 , pp. 243-263
    • El-Abd, M.1
  • 29
    • 84901190234 scopus 로고    scopus 로고
    • A comprehensive survey: artificial bee colony (abc) algorithm and applications
    • Karaboga D, Gorkemli B, Ozturk C, Karaboga N (2014) A comprehensive survey: artificial bee colony (abc) algorithm and applications. Artif Intell Rev 42(1):21–57
    • (2014) Artif Intell Rev , vol.42 , Issue.1 , pp. 21-57
    • Karaboga, D.1    Gorkemli, B.2    Ozturk, C.3    Karaboga, N.4
  • 32
    • 77957901422 scopus 로고    scopus 로고
    • A novel clustering approach: artificial bee colony (ABC) algorithm
    • Karaboga Dervis, Ozturk Celal (2011) A novel clustering approach: artificial bee colony (ABC) algorithm. Appl Soft Comput 11(1):652–657
    • (2011) Appl Soft Comput , vol.11 , Issue.1 , pp. 652-657
    • Karaboga, D.1    Ozturk, C.2
  • 33
    • 84879015433 scopus 로고    scopus 로고
    • Parameter selection in particle swarm optimization
    • Lecture Notes in Computer Science. Springer, Heidelberg:
    • Shi Yuhui, Eberhart Russell C (1998) Parameter selection in particle swarm optimization. In: Evolutionary Programming VII, volume 1447 Lecture Notes in Computer Science. Springer, Heidelberg, pp 591–600
    • (1998) Evolutionary Programming VII , vol.1447 , pp. 591-600
    • Yuhui, S.1    Eberhart Russell, C.2
  • 37
    • 0035995715 scopus 로고    scopus 로고
    • Comparing predictive accuracy
    • Diebold FX, Mariano RS (2002) Comparing predictive accuracy. J Bus Econ Stat 20(1):134–144
    • (2002) J Bus Econ Stat , vol.20 , Issue.1 , pp. 134-144
    • Diebold, F.X.1    Mariano, R.S.2
  • 38
    • 77149138054 scopus 로고    scopus 로고
    • Application of svr with improved ant colony optimization algorithms in exchange rate forecasting
    • Hung Wei-Mou, Hong Wei-Chiang (2009) Application of svr with improved ant colony optimization algorithms in exchange rate forecasting. Control Cybern 38(3):863–891
    • (2009) Control Cybern , vol.38 , Issue.3 , pp. 863-891
    • Hung, W.-M.1    Hong, W.-C.2
  • 39
    • 80052103053 scopus 로고    scopus 로고
    • Electric load forecasting by seasonal recurrent svr (support vector regression) with chaotic artificial bee colony algorithm
    • Hong Wei-Chiang (2011) Electric load forecasting by seasonal recurrent svr (support vector regression) with chaotic artificial bee colony algorithm. Energy 36(9):5568–5578
    • (2011) Energy , vol.36 , Issue.9 , pp. 5568-5578
    • Hong, W.-C.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.