REFERENCES

1. Schwartz R, Dodge J, Smith NA, Etzioni O. Green AI. Commun ACM 2020;63:54-63.

2. Candelieri A, Perego R, Archetti F. Green machine learning via augmented Gaussian processes and multi-information source optimization. Soft Comput 2021;25:12591-603.

3. Castanyer RC, Martínez-Fernández S, Franch X. Which design decisions in AI-enabled mobile applications contribute to greener AI? Available from: https://arxiv.org/abs/2109.15284 [Last accessed on 30 Dec 2022].

4. Tornede T, Tornede A, Hanselle J, Wever M, Mohr F, Hüllermeier E. Towards green automated machine learning: status quo and future directions. Available from: https://arxiv.org/abs/2111.05850 [Last accessed on 30 Dec 2022].

5. Vale Z, Gomes L, Ramos D, Faria P. Green computing: a realistic evaluation of energy consumption for building load forecasting computation. J Smart Environ Green Comput 2022;2:34-45.

6. Barredo Arrieta A, Díaz-rodríguez N, Del Ser J, et al. Explainable Artificial Intelligence (XAI): concepts, taxonomies, opportunities and challenges toward responsible AI. Inf Fusion 2020;58:82-115.

7. der Waa J, Nieuwburg E, Cremers A, Neerincx M. Evaluating XAI: a comparison of rule-based and example-based explanations. Artif Intell 2021;291:103404.

8. Pan SJ, Yang Q. A survey on transfer learning. IEEE Trans Knowl Data Eng 2010;22:1345-59.

9. Pan SJ, Zheng VW, Yang Q, Hu DH, Transfer learning for wifi-based indoor localization. Available from: https://www.aaai.org/Papers/Workshops/2008/WS-08-13/WS08-13-008.pdf [Last accessed on 30 Dec 2022].

10. Lu J, Zuo H, Zhang G. Fuzzy Multiple-Source Transfer Learning. IEEE Trans Fuzzy Syst 2020;28:3418-31.

11. Zuo H, Zhang G, Pedrycz W, Behbood V, Lu J. Fuzzy regression transfer learning in takagi-sugeno fuzzy models. IEEE Trans Fuzzy Syst 2017;25:1795-807.

12. Abdulrahman S, Tout H, Ould-slimane H, Mourad A, Talhi C, Guizani M. A Survey on federated learning: the journey from centralized to distributed on-site learning and beyond. IEEE Internet Things J 2021;8:5476-97.

13. Hu X, Shen Y, Pedrycz W, Wang X, Gacek A, Liu B. Identification of fuzzy rule-based models with collaborative fuzzy clustering. IEEE Trans Cybern 2022;52:6406-19.

14. Kairouz P, Mcmahan HB, Avent B, et al. Advances and open problems in federated learning. FNT Mach Learn 2021;14:1-210.

15. Yang Q, Liu Y, Cheng Y, Kang Y, Chen T, Yu H. Federated learning. Synth Lect Artif Intell Mach Learn 2019;13:1-207.

16. . Federated learning. In: Yang Q, Fan L, Yu H, editors. Privacy and incentive, Springer; 2020.

17. Pedrycz W. Granular computing: analysis and design of intelligent systems. Boca Raton: CRC press; 2013.

18. Pedrycz W. Granular computing for data analytics: a manifesto of human-centric computing. IEEE/CAA J Autom Sinica 2018;5:1025-34.

19. Pedrycz W. An introduction to computing with fuzzy sets. IEEE ASSP Magazine; 2021.

20. Zadeh LA. Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets Syst 1997;90:111-27.

21. Moore RE. Introduction to interval computations (Götz Alefeld and Jürgen Herzberger). SIAM Rev 1985;27:296-7.

22. Hinton G, Vinyals O, Dean J. Distilling the knowledge in a neural network. arXiv preprint arXiv:1503.02531 2015:2.

23. Box GEP. Science and statistics. J Am Stat Assoc 1976;71:791-9.