Application of artificial bee colony algorithm for inverse modelling of a solar collector

References

• Sekhar YR, Sharma KV, Rao MB. Evaluation of heat loss coefficients in solar flat plate collectors. ARPN J. Eng. Appl. Sci. 2009;4:15–19.
   Google Scholar
• Jiandong Z, Hanzhong T, Susu C. Numerical simulation for structural parameters of flat-plate solar collector. Sol. Energy. 2015;117:192–202.10.1016/j.solener.2015.04.027
   Web of Science ®Google Scholar
• Visa I, Duta A, Comsit M, et al. Design and experimental optimisation of a novel flat plate solar thermal collector with trapezoidal shape for facades integration. Appl. Therm. Eng. 2015;90:432–443.10.1016/j.applthermaleng.2015.06.026
   Web of Science ®Google Scholar
• Yang Y, Wang Q, Xiu D, et al. A building integrated solar collector: all-ceramic solar collector. Energy Build. 2013;62:15–17.10.1016/j.enbuild.2013.03.002
   Web of Science ®Google Scholar
• Zhai XQ, Wang RZ, Dai YJ, et al. Solar integrated energy system for a green building. Energy Build. 2007;39:985–993.10.1016/j.enbuild.2006.11.010
   Web of Science ®Google Scholar
• Neagoe M, Visa I, Burduhos BG, et al. Thermal load based adaptive tracking for flat plate solar collectors. Energy Procedia. 2014;48:1401–1411.10.1016/j.egypro.2014.02.158
   Google Scholar
• Chen G, Doroshenko A, Koltun P, et al. Comparative field experimental investigations of different flat plate solar collectors. Sol. Energy. 2015;115:577–588.10.1016/j.solener.2015.03.021
   Web of Science ®Google Scholar
• Deng J, Xu Y, Yang X. A dynamic thermal performance model for flat-plate solar collectors based on the thermal inertia correction of the steady-state test method. Renew. Eng. 2015;76:679–686. 10.1016/j.renene.2014.12.005
   Web of Science ®Google Scholar
• Usmani AY, Akhtar N. Existing correlations of top heat loss factor of flat plate solar collectors and impact on useful energy. Int. J. Emergency Technol. Adv. Eng. 2013;3:607–612.
   Google Scholar
• Das R. Inverse study of double-glazed solar collector using hybrid evolutionary algorithm. IEEE Seventh International Conference on Contemporary Computing (IC3); Noida, India. 2014. p. 571–576.
   Google Scholar
• Noh M-H, Lee S-Y. A bivariate Gaussian function approach for inverse cracks identification of forced-vibrating bridge decks. Inverse Probl. Sci. Eng. 2013;21:1047–1073.10.1080/17415977.2012.727086
   Web of Science ®Google Scholar
• Das R, Ooi KT. Predicting multiple combination of parameters for designing a porous fin subjected to a given temperature requirement. Energy Convers. Manage. 2013;66:211–219. 10.1016/j.enconman.2012.10.019
   Web of Science ®Google Scholar
• Choi J-H, Jung Y-J, Jung H-K, et al. A new multimodal cortical source imaging algorithm for integrating simultaneously recorded EEG and MEG. Inverse Probl. Sci. Eng. 2013;21:1074–1089.10.1080/17415977.2012.731596
   Web of Science ®Google Scholar
• El Zahab Z, Divo E, Kassab A. A meshless CFD approach for evolutionary shape optimization of bypass grafts anastomoses. Inverse Probl. Sci. Eng. 2009;17:411–435. 10.1080/17415970902765434
   Web of Science ®Google Scholar
• Zhang S, Liu S. A novel artificial bee colony algorithm for function optimization. Math. Probl. Eng. 2015;2015:1–10.
   Web of Science ®Google Scholar
• Dorigo M, Maniezzo VV, Colorni A. Positive feedback as a search strategy. Technical report 91-016. Italy: Politecnico di Milano; 1991.
   Google Scholar
• Kennedy J, Eberhart R. Particle swarm optimization. IEEE International Conference on Neural Networks; Perth, Australia; 1995. p. 1942–1948.
   Google Scholar
• Li XL. A new intelligent optimization-artificial fish swarm algorithm [Dr. thesis]. Zhejiang: Zhejiang Univ; 2003.
   Google Scholar
• Karaboga D. An idea based on honey bee swarm for numerical optimization. Technical report, Erciyes university, Engineering Faculty, Computer Engineering Department, Kayseri, Turkey; 2005.
   Google Scholar
• Yang X-S, Deb S. Cuckoo search via lévy flights. World Congress on Nature & Biologically Inspired Computing (NaBIC 2009); Coimbatore, India. 2009. p. 210–214. 10.1109/NABIC.2009.5393690
   Google Scholar
• Yang X-S. A new metaheuristic bat-inspired algorithm. Nature inspired cooperative strategies for optimization (NICSO 2010). Heidelberg: Springer; 2010:65–74.
   Google Scholar
• Yang X-S. Nature-inspired metaheuristic algorithms. Frome: Luniver Press; 2010.
   Google Scholar
• Karaboga D, Akay B. A survey: algorithms simulating bee swarm intelligence. Artif. Intell. Rev; 2009;31:61–85.
   Web of Science ®Google Scholar
• Karaboga D, Gorkemli B, Ozturk C, et al. A comprehensive survey: artificial bee colony (ABC) algorithm and applications. Artif. Intell. Rev. 2014;42:21–57. 10.1007/s10462-012-9328-0
   Web of Science ®Google Scholar
• Gerhardt E, Gomes HM. Artificial bee colony (ABC) algorithm for engineering optimization problems. International Conference on Engineering Optimization; Rio de Janeiro, Brazil; 2012. p. 1–11.
   Google Scholar
• Muthiah A, Rajkumar R. A comparison of artificial bee colony algorithm and genetic algorithm to minimize the makespan for job shop scheduling. Procedia Eng. 2014;97:1745–1754.
   Google Scholar
• Neuer G. Spectral and total emissivity measurements of highly emitting materials. Int. J. Thermophys. 1995;16-16:257–265.10.1007/BF01438976
   Web of Science ®Google Scholar
• Choudhury BJ, Schmugge TJ, Chang A, et al. Effect of surface roughness on the microwave emission from soils. J. Geophys. Res. 1979;84:5699–5706. 10.1029/JC084iC09p05699
   Web of Science ®Google Scholar
• Samdarshi SK, Mullick SC. Analysis of the top heat loss factor of flat plate solar collectors with single and double glazing. Int. J. Energy Res. 1990;14:975–990.10.1002/(ISSN)1099-114X
   Web of Science ®Google Scholar
• Samdarshi SK, Mullick SC. Analytical equation for the top heat loss factor of a flat-plate collector with double glazing. J. Sol. Energy Eng. 1991;113:117–122.10.1115/1.2929955
   Web of Science ®Google Scholar
• Karaboga D, Akay B, Ozturk C. Artificial bee colony (ABC) optimization algorithm for training feed-forward neural networks. Model Decis. Artif. Intell. 2007;4617:318–329.
   Google Scholar
• Karaboga D, Basturk B. On the performance of artificial bee colony (ABC) algorithm. Appl. Soft Comput. 2008;8:687–697.10.1016/j.asoc.2007.05.007
   Web of Science ®Google Scholar
• Beck JV, Dinwiddie RB. Parameter estimation method for flash thermal diffusivity with two different heat transfer coefficients. In Thermal Conductivity. Nashville (TN): Technomic Publishing Company; 1996. p. 107–118.
   Google Scholar
• Das R. A simplex search method for a conductive–convective fin with variable conductivity. Int. J. Heat Mass Transfer. 2011;54:5001–5009.10.1016/j.ijheatmasstransfer.2011.07.014
   Web of Science ®Google Scholar
• Ajith M, Das R, Uppaluri R, et al. Boundary surface heat fluxes in a square enclosure with an embedded design element. J. Thermophys. Heat Transfer. 2010;24:845–849.10.2514/1.49910
   Web of Science ®Google Scholar
• Das R. A simulated annealing-based inverse computational fluid dynamics model for unknown parameter estimation in fluid flow problem. Int. J. Comput. Fluid Dynamics. 2012;26:499–513.10.1080/10618562.2011.632375
   Web of Science ®Google Scholar
• Singla RK, Singh K, Das R. Tower characteristics correlation and parameter retrieval in wet-cooling tower with expanded wire mesh packing. Appl. Thermal Eng. 2016;96:240–249.10.1016/j.applthermaleng.2015.11.063
   Web of Science ®Google Scholar