Closure to “ANFIS Modeling with ICA, BBO, TLBO, and IWO Optimization Algorithms and Sensitivity Analysis for Predicting Daily Reference Evapotranspiration” by Maryam Zeinolabedini Rezaabad, Sadegh Ghazanfari, and Maryam Salajegheh
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References
Abdulshahed, A. M., A. P. Longstaff, and S. Fletcher. 2015. “The application of ANFIS prediction models for thermal error compensation on CNC machine tools.” Appl. Soft Comput. 27 (Feb): 158–168. https://doi.org/10.1016/j.asoc.2014.11.012.
Akbari, S., S. M. Mahmood, I. M. Tan, and H. Hematpour. 2018. “Comparison of neuro-fuzzy network and response surface methodology pertaining to the viscosity of polymer solutions.” J. Pet. Explor. Prod. Technol. 8 (3): 887–900. https://doi.org/10.1007/s13202-017-0375-6.
Al-Hmouz, A., J. Shen, R. Al-Hmouz, and J. Yan. 2011. “Modeling and simulation of an adaptive neuro-fuzzy inference system (ANFIS) for mobile learning.” IEEE Trans. Learn. Technol. 5 (3): 226–237. https://doi.org/10.1109/TLT.2011.36.
Alizamir, M., S. Kim, O. Kisi, and M. Zounemat-Kermani. 2020. “A comparative study of several machine learning based non-linear regression methods in estimating solar radiation: Case studies of the USA and Turkey regions.” Energy 197 (Apr): 117239. https://doi.org/10.1016/j.energy.2020.117239.
Deneme, I. O. 2013. “Estimation of modal damping ratio of impact-damped flexible beams using ANFIS.” Neural Comput. Appl. 23 (6): 1669–1676. https://doi.org/10.1007/s00521-012-1126-8.
Ebtehaj, I., H. Bonakdari, and M. S. Es-haghi. 2019. “Design of a hybrid ANFIS–PSO model to estimate sediment transport in open channels.” Iranian J. Sci. Technol. Trans. Civ. Eng. 43 (4): 851–857. https://doi.org/10.1007/s40996-018-0218-9.
Gill, J., J. Singh, O. S. Ohunakin, D. S. Adelekan, O. E. Atiba, M. O. Nkiko, and A. A. Atayero. 2020. “Adaptive neuro-fuzzy inference system (ANFIS) approach for the irreversibility analysis of a domestic refrigerator system using nanolubricant.” Energy Rep. 6 (Nov): 1405–1417. https://doi.org/10.1016/j.egyr.2020.05.016.
Gori, M., and A. Tesi. 1992. “On the problem of local minima in backpropagation.” IEEE Trans. Pattern Anal. Mach. Intell. 14 (1): 76–86. https://doi.org/10.1109/34.107014.
Gorzalczany, M. B. 2012. Computational intelligence systems and applications: Neuro-fuzzy and fuzzy neural synergisms Physica. Berlin: Springer.
Goyal, M. K., B. Bharti, J. Quilty, J. Adamowski, and A. Pandey. 2014. “Modeling of daily pan evaporation in sub tropical climates using ANN, LS-SVR, Fuzzy Logic, and ANFIS.” Expert Syst. Appl. 41 (11): 5267–5276. https://doi.org/10.1016/j.eswa.2014.02.047.
Kiran, T. R., and S. P. S. Rajput. 2011. “An effectiveness model for an indirect evaporative cooling (IEC) system: Comparison of artificial neural networks (ANN), adaptive neuro-fuzzy inference system (ANFIS) and fuzzy inference system (FIS) approach.” Appl. Soft Comput. 11 (4): 3525–3533. https://doi.org/10.1016/j.asoc.2011.01.025.
Mehrabian, A. R., and C. Lucas. 2006. “A novel numerical optimization algorithm inspired from weed colonization.” Ecol. Inf. 1 (4): 355–366. https://doi.org/10.1016/j.ecoinf.2006.07.003.
Najafzadeh, M., and G. Oliveto. 2020. “Riprap incipient motion for overtopping flows with machine learning models.” J. Hydroinf. 22 (4): 749–767. https://doi.org/10.2166/hydro.2020.129.
Najafzadeh, M., and M. Zeinolabedini. 2019. “Prognostication of waste water treatment plant performance using efficient soft computing models: An environmental evaluation.” Measurement 138 (May): 690–701. https://doi.org/10.1016/j.measurement.2019.02.014.
Nourani, V., and M. Komasi. 2013. “A geomorphology-based ANFIS model for multi-station modeling of rainfall–runoff process.” J. Hydrol. 490 (May): 41–55. https://doi.org/10.1016/j.jhydrol.2013.03.024.
Orgun, M. A., and J. Thornton. 2007. “AI 2007: Advances in artificial intelligence.” In Proc., 20th Australian Joint Conf. on Artificial Intelligence. Berlin: Springer.
Rao, R. V., V. J. Savsani, and D. P. Vakharia. 2012. “Teaching–learning-based optimization: An optimization method for continuous non-linear large scale problems.” Inf. Sci. 183 (1): 1–15. https://doi.org/10.1016/j.ins.2011.08.006.
Rezaei, H., M. Rahmati, and H. Modarress. 2017. “Application of ANFIS and MLR models for prediction of methane adsorption on and faujasite zeolites: Effect of cations substitution.” Neural Comput. Appl. 28 (2): 301–312. https://doi.org/10.1007/s00521-015-2057-y.
Sadeghi, G., M. Najafzadeh, and H. Safarzadeh. 2020. “Utilizing gene-expression programming in modelling the thermal performance of evacuated tube solar collectors.” J. Storage Mater. 30 (Aug): 101546. https://doi.org/10.1016/j.est.2020.101546.
Shahin Mohamed, A., R. Maier Holger, and B. Jaksa Mark. 2004. “Data division for developing neural networks applied to geotechnical engineering.” J. Comput. Civ. Eng. 18 (2): 105–114. https://doi.org/10.1061/(ASCE)0887-3801(2004)18:2(105).
Shiri, J., W. Dierickx, A. Baba, S. Neamati, and M. A. Ghorbani. 2011. “Estimating daily pan evaporation from climatic data of the state of Illinois, USA using adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN).” Hydrol. Res. 42 (6): 491–502. https://doi.org/10.2166/nh.2011.020.
Simon, D. 2008. “Biogeography-based optimization.” IEEE Trans. Evol. Comput. 12 (6): 702–713. https://doi.org/10.1109/TEVC.2008.919004.
Tran, N. T., N. Le Chau, and T.-P. Dao. 2020. “An effective hybrid approach of desirability, fuzzy logic, ANFIS and LAPO algorithm for optimizing compliant mechanism.” Eng. Comput. 2020 (Feb): 1–31. https://doi.org/10.1007/s00366-020-00963-7.
Valipour, M. 2017. “Calibration of mass transfer-based models to predict reference crop evapotranspiration.” Appl. Water Sci. 7 (2): 625–635. https://doi.org/10.1007/s13201-015-0274-2.
Younes, M. K., Z. M. Nopiah, N. E. A. Basri, H. Basri, and M. F. M. Abushammala. 2015. “Solid waste forecasting using modified ANFIS modeling.” J. Air Waste Manage. Assoc. 65 (10): 1229–1238. https://doi.org/10.1080/10962247.2015.1075919.
Yu, X. 1992. “Can backpropagation error surface not have local minima.” IEEE Trans. Neural Networks 3 (6): 1019–1021. https://doi.org/10.1109/72.165604.
Yu, X.-H., and G.-A. Chen. 1995. “On the local minima free condition of backpropagation learning.” IEEE Trans. Neural Networks. 6 (5): 1300–1303. https://doi.org/10.1109/72.410380.
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Received: Dec 10, 2020
Accepted: Aug 11, 2021
Published online: Sep 28, 2021
Published in print: Dec 1, 2021
Discussion open until: Feb 28, 2022
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