Erratum to A linear genetic programming approach for the prediction of solar global radiation (Neural Comput & Applic, 10.1007/s00521-012-1039-6);A linear genetic programming approach for the prediction of solar global radiation

Neural Computing and Applications

Volumn 23, Issue 3-4, 2013, Pages 1197-1204

  Shavandi, Hassan ^a   Saeedi Ramyani, Sara ^a  

^a SHARIF UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Climatological parameters; Linear genetic programming; Prediction; Solar global radiation

Indexed keywords

ATMOSPHERIC RADIATION; FORECASTING; GENETIC ALGORITHMS; SENSITIVITY ANALYSIS; SOLAR RADIATION;

CLIMATOLOGICAL PARAMETERS; LINEAR GENETIC PROGRAMMING; METEOROLOGICAL PARAMETERS; SOLAR GLOBAL RADIATION; TEST DATA;

GENETIC PROGRAMMING;

EID: 84884590246     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-012-1128-6     Document Type: Erratum

References (35)

1. Azadeh A, Maghsoudi A, Sohrabkhani S (2009) An integrated artificial neural networks approach for predicting global radiation. Energy Convers Manage 50: 1497-1505.
2. Alam MS, Saha SK, Chowdhury MAK, Saifuzzaman M, Rahman M (2005) Simulation of solar radiation system. Am J Appl Sci 2(4): 751-758.
3. Al-Salihi AM, Kadum MM, Mohammed AJ (2010) Estimation of global solar radiation on horizontal surface using meteorological measurement for different cities in Iraq. Asian J Scient Res 3(4): 240-248.
4. Box GEP, Jenkins G (1970) Time series analysis: forecasting and control. Holden-Day, San Francisco.
5. Wu J, Chan CK (2011) Prediction of hourly solar radiation using a novel hybrid model of ARMA and TDNN. Sol Energy 85: 808-817.
6. Behrang MA, Assareh E, Noghrehabadi AR, Ghanbarzadeh A (2011) New sunshine-based models for predicting global solar radiation using PSO (particle swarm optimization) technique. Energy 36(5): 3036-3049.
7. Chakraverty S, Gupta P (2008) Comparison of neural network configurations in the long-range forecast of southwest monsoon rainfall over India. Neural Comput Appl 17(2): 187-192.
8. El-Shafie A, Abdelazim T, Noureldin A (2010) Neural network modeling of time-dependent creep deformations in masonry structures. Neural Comput Appl 19: 583-594.
9. Chakraverty S, Gupta P, Sharma S (2010) Neural network-based simulation for response identification of two-storey shear building subject to earthquake motion. Neural Comput Appl 19: 367-375.
10. Kraslawski A, Pedrycz W, Nyström L (1999) Fuzzy neural network as instance generator for case-based reasoning system: an example of selection of heat exchange equipment in mixing. Neural Comput Appl 8(2): 106-113.
11. Cao M, Qiao P (2008) Neural network committee-based sensitivity analysis strategy for geotechnical engineering problems. Neural Comput Appl 17: 509-519.
12. Alavi AH, Gandomi AH (2011) Prediction of principal ground-motion parameters using a hybrid method coupling artificial neural networks and simulated annealing. Comput Struct 89(23-24): 2176-2194.
13. Alavi AH, Gandomi AH, Mollahasani A, Heshmati AAR, Rashed A (2010) Modeling of maximum dry density and optimum moisture content of stabilized soil using artificial neural networks. J Plant Nutr Soil Sci 173(3): 368-379.
14. Al-Alawi SM, Al-Hinai HA (1998) An ANN approach for predicting global radiation in locations with no direct measurement instrumentation. Renew Energy 14: 199-204.
15. Lopez G, Rubio MA, Martinez M, Batlles FJ (2001) Estimation of hourly global photosynthetically active radiation using artificial neural network models. Agri Forest Meteorol 107: 279-291.
16. Sozen A, Arcakli{dotless}oglu E, Ozalp M, Galip Kanit E (2005) Solar-energy potential in Turkey. Appl Energy 80: 367-381.
17. Ozgoren M, Bilgili M, Sahin B (2012) Estimation of global solar radiation using ANN over Turkey. Exp Sys Appl 39: 5043-5051.
18. Alavi AH, Gandomi AH (2011) A robust data mining approach for formulation of geotechnical engineering systems. Eng Comput 28(3): 242-274.
19. Koza JR (1992) Genetic programming, on the programming of computers by means of natural selection. MIT Press, Cambridge.
20. Banzhaf W, Nordin P, Keller R, Francone F (1998) Genetic programming-an introduction on the automatic evolution of computer programs and its application. Morgan Kaufmann, Heidelberg.
21. Alavi AH, Gandomi AH, Sahab MG, Gandomi M (2010) Multi expression programming: a new approach to formulation of soil classification. Eng Comput 26(2): 111-118.
22. Gandomi AH, Alavi AH (2011) Multi-stage genetic programming: a new strategy to nonlinear system modeling. Inf Sci 181(23): 5227-5239.
23. Gandomi AH, Alavi AH (2012) A new multi-gene genetic programming approach to nonlinear system modeling. Part I: materials and structural engineering problems. Neur Comput Appl 21: 171-187.
24. Gandomi AH, Alavi AH, Sadat Hosseini SS (2008) Discussion on genetic programming for retrieving missing information in wave records along the west coast of India. Appl Ocean Res 30(4): 338-339.
25. Brameier M, Banzhaf W (2007) Linear genetic programming. Springer, New York.
26. Brameier M, Banzhaf W (2001) A comparison of linear genetic programming and neural networks in medical data mining. IEEE T Evolut Comput 5(1): 17-26.
27. Alavi AH, Heshmati AAR, Gandomi AH, Askarinejad A, Mirjalili M (2008) Utilisation of computational intelligence techniques for stabilised soil. In: Proceedings of the 6th international conference on engineering computational technology, Civil-Comp Press, United Kingdom, Paper no. 175.
28. Alavi AH, Gandomi AH (2012) Energy-based models for assessment of soil liquefaction. Geosci Front 3(4): 541-555.
29. Gandomi AH, Alavi AH, Mousavi M, Tabatabaei SM (2011) A Hybrid computational approach to derive new ground-motion attenuation models. Eng Appl Artif Intell 24(4): 717-732.
30. Gandomi AH, Alavi AH, Sahab MG (2010) New formulation for compressive strength of CFRP confined concrete cylinders using linear genetic programming. Mater Struct 43(7): 963-983.
31. Gandomi AH, Alavi AH, Yun GJ (2011) Nonlinear modeling of shear strength of SFRCB beams using linear genetic programming. Struct Eng Mech 38(1): 1-25.
32. Conrads M, Dolezal O, Francone FD, Nordin P (2004) Discipulus Lite™-fast genetic programming based on AIM learning technology. Register Machine Learning Technologies Inc, Littleton, CO.
33. Smith GN (1986) Probability and statistics in civil engineering. Collins, London.
34. Angstrom A (1924) Solar and terrestrial radiation. QJR Meteorol Soc 50: 121-125.
35. Alavi AH, Ameri M, Gandomi AH, Mirzahosseini MR (2011) Formulation of flow number of asphalt mixes using a hybrid computational method. Constr Build Mater 25(3): 1338-1355.