메뉴 건너뛰기




Volumn 77, Issue 2, 2015, Pages 1055-1068

Retraction Note to: Potential of support vector regression for solar radiation prediction in Nigeria (Natural Hazards, (2015), 77, 2, (1055-1068), 10.1007/s11069-015-1641-x);Potential of support vector regression for solar radiation prediction in Nigeria

Author keywords

Nigeria; Soft computing methodologies; Solar radiation; Sunshine hour; SVR

Indexed keywords


EID: 84939934489     PISSN: 0921030X     EISSN: 15730840     Source Type: Journal    
DOI: 10.1007/s11069-020-03956-3     Document Type: Erratum
Times cited : (40)

References (48)
  • 1
    • 84890067165 scopus 로고    scopus 로고
    • New model to estimate daily global solar radiation over Nigeria
    • Ajayi O et al (2014) New model to estimate daily global solar radiation over Nigeria. Sustain Energy Technol Assess 5:28–36
    • (2014) Sustain Energy Technol Assess , vol.5 , pp. 28-36
    • Ajayi, O.1
  • 2
    • 84882258567 scopus 로고    scopus 로고
    • Comparative study of stand-alone and hybrid solar energy systems suitable for off-grid rural electrification: a review
    • Akikur R et al (2013) Comparative study of stand-alone and hybrid solar energy systems suitable for off-grid rural electrification: a review. Renew Sustain Energy Rev 27:738–752
    • (2013) Renew Sustain Energy Rev , vol.27 , pp. 738-752
    • Akikur, R.1
  • 3
    • 0037241784 scopus 로고    scopus 로고
    • Relationship between global solar radiation and sunshine duration for Onne, Nigeria
    • Akpabio LE, Etuk SE (2003) Relationship between global solar radiation and sunshine duration for Onne, Nigeria. Turk J Phys 27:161–167
    • (2003) Turk J Phys , vol.27 , pp. 161-167
    • Akpabio, L.E.1    Etuk, S.E.2
  • 4
    • 84882706537 scopus 로고    scopus 로고
    • Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. FAO
    • Allen RG et al (1998) Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. FAO, Rome, vol 300, p 6541
    • (1998) Rome , vol.300 , pp. 6541
    • Allen, R.G.1
  • 5
    • 0032075864 scopus 로고    scopus 로고
    • An ANN-based approach for predicting global radiation in locations with no direct measurement instrumentation
    • Al-Alawi S, Al-Hinai H (1998) An ANN-based approach for predicting global radiation in locations with no direct measurement instrumentation. Renewable Energy 14(1):199–204
    • (1998) Renewable Energy , vol.14 , Issue.1 , pp. 199-204
    • Al-Alawi, S.1    Al-Hinai, H.2
  • 6
    • 84870240528 scopus 로고    scopus 로고
    • Batch-mode semi-supervised active learning for statistical machine translation
    • Ananthakrishnan S et al (2013) Batch-mode semi-supervised active learning for statistical machine translation. Comput Speech Lang 27(2):397–406
    • (2013) Comput Speech Lang , vol.27 , Issue.2 , pp. 397-406
    • Ananthakrishnan, S.1
  • 7
    • 84944484637 scopus 로고
    • Solar and terrestrial radiation. Report to the international commission for solar research on actinometric investigations of solar and atmospheric radiation
    • Angstrom A (1924) Solar and terrestrial radiation. Report to the international commission for solar research on actinometric investigations of solar and atmospheric radiation. Q J R Meteorol Soc 50(210):121–126
    • (1924) Q J R Meteorol Soc , vol.50 , Issue.210 , pp. 121-126
    • Angstrom, A.1
  • 8
    • 78549234303 scopus 로고    scopus 로고
    • Sustainable electricity generation for rural and peri-urban populations of sub-Saharan Africa: the “flexy-energy” concept
    • Azoumah Y et al (2011) Sustainable electricity generation for rural and peri-urban populations of sub-Saharan Africa: the “flexy-energy” concept. Energy Policy 39(1):131–141
    • (2011) Energy Policy , vol.39 , Issue.1 , pp. 131-141
    • Azoumah, Y.1
  • 9
    • 84858709997 scopus 로고    scopus 로고
    • Hybrid renewable energy systems for power generation in stand-alone applications: a review
    • Bajpai P, Dash V (2012) Hybrid renewable energy systems for power generation in stand-alone applications: a review. Renew Sustain Energy Rev 16(5):2926–2939
    • (2012) Renew Sustain Energy Rev , vol.16 , Issue.5 , pp. 2926-2939
    • Bajpai, P.1    Dash, V.2
  • 10
    • 79955670335 scopus 로고    scopus 로고
    • New sunshine-based models for predicting global solar radiation using PSO (particle swarm optimization) technique
    • Behrang M et al (2011) New sunshine-based models for predicting global solar radiation using PSO (particle swarm optimization) technique. Energy 36(5):3036–3049
    • (2011) Energy , vol.36 , Issue.5 , pp. 3036-3049
    • Behrang, M.1
  • 11
    • 65649123894 scopus 로고    scopus 로고
    • ANN-based modelling and estimation of daily global solar radiation data: a case study
    • Benghanem M, Mellit A, Alamri S (2009) ANN-based modelling and estimation of daily global solar radiation data: a case study. Energy Convers Manag 50(7):1644–1655
    • (2009) Energy Convers Manag , vol.50 , Issue.7 , pp. 1644-1655
    • Benghanem, M.1    Mellit, A.2    Alamri, S.3
  • 12
    • 84874853060 scopus 로고    scopus 로고
    • Empirical models for estimating global solar radiation: a review and case study
    • Besharat F, Dehghan AA, Faghih AR (2013) Empirical models for estimating global solar radiation: a review and case study. Renew Sustain Energy Rev 21:798–821
    • (2013) Renew Sustain Energy Rev , vol.21 , pp. 798-821
    • Besharat, F.1    Dehghan, A.A.2    Faghih, A.R.3
  • 13
    • 48549111629 scopus 로고
    • On the relationship between incoming solar radiation and daily maximum and minimum temperature
    • Bristow KL, Campbell GS (1984) On the relationship between incoming solar radiation and daily maximum and minimum temperature. Agric For Meteorol 31(2):159–166
    • (1984) Agric For Meteorol , vol.31 , Issue.2 , pp. 159-166
    • Bristow, K.L.1    Campbell, G.S.2
  • 14
    • 84872619870 scopus 로고    scopus 로고
    • Estimation of monthly average daily solar radiation from measured meteorological data in Yangtze River Basin in China
    • Chen JL, Li GS (2013) Estimation of monthly average daily solar radiation from measured meteorological data in Yangtze River Basin in China. Int J Climatol 33(2):487–498
    • (2013) Int J Climatol , vol.33 , Issue.2 , pp. 487-498
    • Chen, J.L.1    Li, G.S.2
  • 15
    • 0019438277 scopus 로고
    • Measured solar radiation in a Nigerian environment compared with predicted data
    • Ezekwe C, Ezeilo CC (1981) Measured solar radiation in a Nigerian environment compared with predicted data. Sol Energy 26(2):181–186
    • (1981) Sol Energy , vol.26 , Issue.2 , pp. 181-186
    • Ezekwe, C.1    Ezeilo, C.C.2
  • 16
    • 0027790301 scopus 로고
    • Total solar radiation estimates in Nigeria using a maximum-likelihood quadratic fit
    • Fagbenle RL (1993) Total solar radiation estimates in Nigeria using a maximum-likelihood quadratic fit. Renewable Energy 3(6):813–817
    • (1993) Renewable Energy , vol.3 , Issue.6 , pp. 813-817
    • Fagbenle, R.L.1
  • 17
    • 84904761881 scopus 로고    scopus 로고
    • Empirical correlations as a means for estimating monthly average daily global radiation: a critical overview
    • Halawa E, GhaffarianHoseini A, Li DHW (2014) Empirical correlations as a means for estimating monthly average daily global radiation: a critical overview. Renewable Energy 72:149–153
    • (2014) Renewable Energy , vol.72 , pp. 149-153
    • Halawa, E.1    GhaffarianHoseini, A.2    Li, D.H.W.3
  • 18
    • 0033118301 scopus 로고    scopus 로고
    • Stochastic daily solar irradiance for biological modeling applications
    • Hansen JW (1999) Stochastic daily solar irradiance for biological modeling applications. Agric For Meteorol 94(1):53–63
    • (1999) Agric For Meteorol , vol.94 , Issue.1 , pp. 53-63
    • Hansen, J.W.1
  • 19
    • 0020434889 scopus 로고
    • Estimating potential evapotranspiration
    • Hargreaves GH, Samani ZA (1982) Estimating potential evapotranspiration. J Irrig Drain Div 108(3):225–230
    • (1982) J Irrig Drain Div , vol.108 , Issue.3 , pp. 225-230
    • Hargreaves, G.H.1    Samani, Z.A.2
  • 20
    • 84857198482 scopus 로고    scopus 로고
    • A review on energy scenario and sustainable energy in Indonesia
    • Hasan M, Mahlia T, Nur H (2012) A review on energy scenario and sustainable energy in Indonesia. Renew Sustain Energy Rev 16(4):2316–2328
    • (2012) Renew Sustain Energy Rev , vol.16 , Issue.4 , pp. 2316-2328
    • Hasan, M.1    Mahlia, T.2    Nur, H.3
  • 21
    • 0032103224 scopus 로고    scopus 로고
    • Estimation of solar radiation for use in crop modelling
    • Hunt L, Kuchar L, Swanton C (1998) Estimation of solar radiation for use in crop modelling. Agric For Meteorol 91(3):293–300
    • (1998) Agric For Meteorol , vol.91 , Issue.3 , pp. 293-300
    • Hunt, L.1    Kuchar, L.2    Swanton, C.3
  • 22
    • 67349229243 scopus 로고    scopus 로고
    • Supervised machine learning algorithms for protein structure classification
    • Jain P, Garibaldi JM, Hirst JD (2009) Supervised machine learning algorithms for protein structure classification. Comput Biol Chem 33(3):216–223
    • (2009) Comput Biol Chem , vol.33 , Issue.3 , pp. 216-223
    • Jain, P.1    Garibaldi, J.M.2    Hirst, J.D.3
  • 23
    • 0027601884 scopus 로고
    • ANFIS: adaptive-network-based fuzzy inference system
    • Jang J-S (1993) ANFIS: adaptive-network-based fuzzy inference system. IEEE Trans Syst Man Cybern 23(3):665–685
    • (1993) IEEE Trans Syst Man Cybern , vol.23 , Issue.3 , pp. 665-685
    • Jang, J.-S.1
  • 24
    • 68349154632 scopus 로고    scopus 로고
    • Computation of monthly mean daily global solar radiation in China using artificial neural networks and comparison with other empirical models
    • Jiang Y (2009) Computation of monthly mean daily global solar radiation in China using artificial neural networks and comparison with other empirical models. Energy 34(9):1276–1283
    • (2009) Energy , vol.34 , Issue.9 , pp. 1276-1283
    • Jiang, Y.1
  • 25
    • 67349096333 scopus 로고    scopus 로고
    • Evaluation of temperature-based global solar radiation models in China
    • Liu X et al (2009) Evaluation of temperature-based global solar radiation models in China. Agric For Meteorol 149(9):1433–1446
    • (2009) Agric For Meteorol , vol.149 , Issue.9 , pp. 1433-1446
    • Liu, X.1
  • 26
    • 49949145327 scopus 로고
    • Notes on the use of the gunn bellani radiometer
    • McCulloch J, Wangati F (1967) Notes on the use of the gunn bellani radiometer. Agric Meteorol 4(1):63–70
    • (1967) Agric Meteorol , vol.4 , Issue.1 , pp. 63-70
    • McCulloch, J.1    Wangati, F.2
  • 27
    • 75449111025 scopus 로고    scopus 로고
    • Artificial Intelligence technique for modelling and forecasting of solar radiation data: a review
    • Mellit A (2008) Artificial Intelligence technique for modelling and forecasting of solar radiation data: a review. Int J Artif intell Soft Comput 1(1):52–76
    • (2008) Int J Artif intell Soft Comput , vol.1 , Issue.1 , pp. 52-76
    • Mellit, A.1
  • 28
    • 33646726754 scopus 로고    scopus 로고
    • An adaptive wavelet-network model for forecasting daily total solar-radiation
    • Mellit A, Benghanem M, Kalogirou S (2006) An adaptive wavelet-network model for forecasting daily total solar-radiation. Appl Energy 83(7):705–722
    • (2006) Appl Energy , vol.83 , Issue.7 , pp. 705-722
    • Mellit, A.1    Benghanem, M.2    Kalogirou, S.3
  • 29
    • 84892951822 scopus 로고    scopus 로고
    • Fighting global warming by climate engineering: Is the Earth radiation management and the solar radiation management any option for fighting climate change?
    • Ming T et al (2014) Fighting global warming by climate engineering: Is the Earth radiation management and the solar radiation management any option for fighting climate change? Renew Sustain Energy Rev 31:792–834
    • (2014) Renew Sustain Energy Rev , vol.31 , pp. 792-834
    • Ming, T.1
  • 30
    • 84866149200 scopus 로고    scopus 로고
    • Modeling global solar radiation using Particle Swarm Optimization (PSO)
    • Mohandes MA (2012) Modeling global solar radiation using Particle Swarm Optimization (PSO). Sol Energy 86(11):3137–3145
    • (2012) Sol Energy , vol.86 , Issue.11 , pp. 3137-3145
    • Mohandes, M.A.1
  • 31
    • 84977823155 scopus 로고    scopus 로고
    • Nigerian Meteorological Agency
    • NIMET (2014) Nigerian Meteorological Agency. htttp://www.nimet.gov.ng
    • (2014) htttp://www.nimet.gov.ng
  • 32
    • 78049281871 scopus 로고    scopus 로고
    • Supervised machine learning and heterotic classification of maize (Zea mays L.) using molecular marker data
    • Ornella L, Tapia E (2010) Supervised machine learning and heterotic classification of maize (Zea mays L.) using molecular marker data. Comput Electron Agric 74(2):250–257
    • (2010) Comput Electron Agric , vol.74 , Issue.2 , pp. 250-257
    • Ornella, L.1    Tapia, E.2
  • 33
    • 84867738691 scopus 로고    scopus 로고
    • Adaptive neuro-fuzzy estimation of autonomic nervous system parameters effect on heart rate variability
    • Petković D, Ćojbašić Ž (2012) Adaptive neuro-fuzzy estimation of autonomic nervous system parameters effect on heart rate variability. Neural Comput Appl 21(8):2065–2070
    • (2012) Neural Comput Appl , vol.21 , Issue.8 , pp. 2065-2070
    • Petković, D.1    Ćojbašić, Ž.2
  • 34
    • 0028873647 scopus 로고
    • A review of satellite methods to derive surface shortwave irradiance
    • Pinker R, Frouin R, Li Z (1995) A review of satellite methods to derive surface shortwave irradiance. Remote Sens Environ 51(1):108–124
    • (1995) Remote Sens Environ , vol.51 , Issue.1 , pp. 108-124
    • Pinker, R.1    Frouin, R.2    Li, Z.3
  • 35
    • 54549091989 scopus 로고    scopus 로고
    • Support vector regression methodology for storm surge predictions
    • Rajasekaran S, Gayathri S, Lee T-L (2008) Support vector regression methodology for storm surge predictions. Ocean Eng 35(16):1578–1587
    • (2008) Ocean Eng , vol.35 , Issue.16 , pp. 1578-1587
    • Rajasekaran, S.1    Gayathri, S.2    Lee, T.-L.3
  • 36
    • 84905867870 scopus 로고    scopus 로고
    • Potential of radial basis function based support vector regression for global solar radiation prediction
    • Ramedani Z et al (2014a) Potential of radial basis function based support vector regression for global solar radiation prediction. Renew Sustain Energy Rev 39:1005–1011
    • (2014) Renew Sustain Energy Rev , vol.39 , pp. 1005-1011
    • Ramedani, Z.1
  • 37
    • 84908135960 scopus 로고    scopus 로고
    • A comparative study between fuzzy linear regression and support vector regression for global solar radiation prediction in Iran
    • Ramedani Z et al (2014b) A comparative study between fuzzy linear regression and support vector regression for global solar radiation prediction in Iran. Sol Energy 109:135–143
    • (2014) Sol Energy , vol.109 , pp. 135-143
    • Ramedani, Z.1
  • 38
    • 0002943125 scopus 로고
    • Empirical models for the correlation of global solar radiation with meteorological data for northern Nigeria
    • Sambo A (1986) Empirical models for the correlation of global solar radiation with meteorological data for northern Nigeria. Sol Wind Technol 3(2):89–93
    • (1986) Sol Wind Technol , vol.3 , Issue.2 , pp. 89-93
    • Sambo, A.1
  • 39
    • 84876586982 scopus 로고    scopus 로고
    • Srivastava S, Bhardwaj S, Sastri O (2012) A novel hybrid model for solar radiation prediction. In International conference on emerging trends in electrical engineering and energy management (ICETEEEM), 2012. IEEE
    • Srivastava S, Bhardwaj S, Sastri O (2012) A novel hybrid model for solar radiation prediction. In International conference on emerging trends in electrical engineering and energy management (ICETEEEM), 2012. IEEE
  • 40
    • 22544436127 scopus 로고    scopus 로고
    • Global solar radiation in Central European lowlands estimated by various empirical formulae
    • Trnka M et al (2005) Global solar radiation in Central European lowlands estimated by various empirical formulae. Agric For Meteorol 131(1):54–76
    • (2005) Agric For Meteorol , vol.131 , Issue.1 , pp. 54-76
    • Trnka, M.1
  • 43
    • 84879322256 scopus 로고    scopus 로고
    • A dynamic particle filter-support vector regression method for reliability prediction
    • Wei Z et al (2013) A dynamic particle filter-support vector regression method for reliability prediction. Reliab Eng Syst Saf 119:109–116
    • (2013) Reliab Eng Syst Saf , vol.119 , pp. 109-116
    • Wei, Z.1
  • 44
    • 30444437204 scopus 로고    scopus 로고
    • Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance
    • Willmott CJ, Matsuura K (2005) Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Clim Res 30(1):79
    • (2005) Clim Res , vol.30 , Issue.1 , pp. 79
    • Willmott, C.J.1    Matsuura, K.2
  • 45
    • 34547106811 scopus 로고    scopus 로고
    • Methods and strategy for modeling daily global solar radiation with measured meteorological data—a case study in Nanchang station, China
    • Wu G, Liu Y, Wang T (2007) Methods and strategy for modeling daily global solar radiation with measured meteorological data—a case study in Nanchang station, China. Energy Convers Manag 48(9):2447–2452
    • (2007) Energy Convers Manag , vol.48 , Issue.9 , pp. 2447-2452
    • Wu, G.1    Liu, Y.2    Wang, T.3
  • 46
    • 67349170327 scopus 로고    scopus 로고
    • Localized support vector regression for time series prediction
    • Yang H et al (2009) Localized support vector regression for time series prediction. Neurocomputing 72(10):2659–2669
    • (2009) Neurocomputing , vol.72 , Issue.10 , pp. 2659-2669
    • Yang, H.1
  • 47
    • 58349091868 scopus 로고    scopus 로고
    • Sentiment classification of online reviews to travel destinations by supervised machine learning approaches
    • Ye Q, Zhang Z, Law R (2009) Sentiment classification of online reviews to travel destinations by supervised machine learning approaches. Expert Syst Appl 36(3):6527–6535
    • (2009) Expert Syst Appl , vol.36 , Issue.3 , pp. 6527-6535
    • Ye, Q.1    Zhang, Z.2    Law, R.3
  • 48
    • 84867884437 scopus 로고    scopus 로고
    • Iterated time series prediction with multiple support vector regression models
    • Zhang L et al (2013) Iterated time series prediction with multiple support vector regression models. Neurocomputing 99:411–422
    • (2013) Neurocomputing , vol.99 , pp. 411-422
    • Zhang, L.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.