Fuzzy-based missing value imputation technique for air pollution data
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Linguistics and Language,Language and Linguistics
Link
https://link.springer.com/content/pdf/10.1007/s10462-022-10168-7.pdf
Reference75 articles.
1. Abbasbandy S, Hajighasemi S (2010) A fuzzy distance between two fuzzy numbers. In: International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems. Springer, pp 376–382
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3. Arowosegbe OO, Röösli M, Künzli N, Saucy A, Adebayo-Ojo TC, Jeebhay MF, Al Dalvie M, de Hoogh K (2021) Comparing methods to impute missing daily ground-level pm10 concentrations between 2010–2017 in south africa. Int J Environ Res Public Health 18(7):3374
4. Bagherian MM, Moradi M, Zarasvandi A, Akbaripoor S, Hassanvand MS (2017) Health benefits of pm 10 reduction in Iran. Int J Biometeorol 61(8):1389–1401
5. Bai Y, Li Y, Wang X, Xie J, Li C (2016) Air pollutants concentrations forecasting using back propagation neural network based on wavelet decomposition with meteorological conditions. Atmos Pollut Res 7(3):557–566
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