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S. Roy and A. Chatterjee
16. Ghorani-Azam A, Riahi-Zanjani B, Balali-Mood M (2016) Effects of air pollution on human
health and practical measures for prevention in Iran. J Res Med Sci 21:65. Published 2016 Sep
1. https://doi.org/10.4103/1735-1995.189646
17. Sherstinsky A (2020) Fundamentals of Recurrent Neural Network (RNN) and Long ShortTerm Memory (LSTM) network. Physica D 404:132306. https://doi.org/10.1016/j.physd.2019.
132306
18. Sharma VK, Nigam U (2020) Modeling and forecasting for Covid-19 growth curve in India.
medRxiv
19. Shekhar H (2020) Prediction of spreads of COVID-19 in India from current trend. medRxiv
20. Agatonovic-Kustrin S, Beresford R (2000) Basic concepts of artificial neural network (ANN)
modeling and its application in pharmaceutical research. J Pharm Biomed Anal 22(5):717–727.
https://doi.org/10.1016/s0731-7085(99)00272-1
21. Bergstra A, Brunekreef B, Burdorf A (2018) The effect of industry-related air pollution on
lung function and respiratory symptoms in school children. Environ Health A Global Access
Sci Source 17:30. https://doi.org/10.1186/s12940-018-0373-2
22. Sinnott RO, Guan Z (2018) Prediction of air pollution through machine learning approaches on
the cloud. In: 2018 IEEE/ACM 5th international conference on big data computing applications
and technologies (BDCAT). Zurich, pp 51–60. https://doi.org/10.1109/BDCAT.2018.00015.
23. Bhalgat P, Bhoite S, Pitare S (2019) Air quality prediction using machine learning algorithms.
Int J Comput Appl Technol Res 8. https://doi.org/10.7753/IJCATR0809.1006
24. Carbajal-Hernández JJ (2012) Assessment and prediction of air quality using fuzzy logic and
autoregressive models. Atmos Environ 60:37–50
25. Nallakaruppan MK, SurejIlango H (2017) Location aware climate sensing and real time data
analysis. In: 2017 world congress on computing and communication technologies (WCCCT).
IEEE
26. Li Y, Chen Q, Zhao H, Wang L, Tao R (2015) Variations in pm10, pm2.5 and pm1.0 in an urban
area of the Sichuan basin and their relation to meteorological factors. Atmosphere 6(1):150–163
27. Mahajan S, Chen L-J, Tsai T-C (2017) An empirical study of PM2.5 forecasting using neural
network. In: IEEE smart world congress, At San Francisco, USA
28. Franklin BA, Brook R, Pope CA (2015) Air pollution and cardiovascular disease. Curr Prob
Cardiol 40(5):207–238. ISSN 0146-2806
29. Bansal M, Aggarwal A, Verma T, Sood A (2019) Air quality index prediction of Delhi using
LSTM. https://doi.org/10.13140/RG.2.2.26885.70884
30. Chang Y-S, Chiao H-T, Abimannan S, Huang Y-P, Tsai Y-T, Lin K-M (2020) An LSTM-based
aggregated model for air pollution forecasting. Atmos Pollut Res 11(8):1451–1463. ISSN
1309-1042. https://doi.org/10.1016/j.apr.2020.05.015
31. Belavadi S, Rajagopal S, Ranjani R, Mohan R (2020) Air quality forecasting using LSTM
RNN and wireless sensor networks. Procedia Comput Sci 170:241–248. https://doi.org/10.
1016/j.procs.2020.03.036
32. Gul S, Khan GM (2020) Forecasting hazard level of air pollutants using LSTM’s. In: Maglogiannis I, Iliadis L, Pimenidis E (eds) Artificial intelligence applications and innovations. AIAI
2020. IFIP advances in information and communication technology, vol 584. Springer, Cham.
https://doi.org/10.1007/978-3-030-49186-4_13
33. Jiao Y, Wang Z, Zhang Y (2019) Prediction of air quality index based on LSTM. In: 2019 IEEE
8th joint international information technology and artificial intelligence conference (ITAIC).
Chongqing, China, pp 17–20. https://doi.org/10.1109/ITAIC.2019.8785602
34. Chaudhary V, Deshbhratar A, Kumar V, Paul D, Samsung (2018) Time series based LSTM
model to predict air pollutant’s concentration for prominent cities in India
35. Kumar A, Goyal P (2013) Forecasting of air quality index in Delhi using neural network based
on principal component analysis. Pure Appl Geophys 170:711–722. https://doi.org/10.1007/
s00024-012-0583-4
36. Chatterjee A, Mukherjee S (2020) The impact of lockdown on GDP growth & COVID-19
spread: insights from a mathematical simulation exercise for India
S. Roy and A. Chatterjee
16. Ghorani-Azam A, Riahi-Zanjani B, Balali-Mood M (2016) Effects of air pollution on human
health and practical measures for prevention in Iran. J Res Med Sci 21:65. Published 2016 Sep
1. https://doi.org/10.4103/1735-1995.189646
17. Sherstinsky A (2020) Fundamentals of Recurrent Neural Network (RNN) and Long ShortTerm Memory (LSTM) network. Physica D 404:132306. https://doi.org/10.1016/j.physd.2019.
132306
18. Sharma VK, Nigam U (2020) Modeling and forecasting for Covid-19 growth curve in India.
medRxiv
19. Shekhar H (2020) Prediction of spreads of COVID-19 in India from current trend. medRxiv
20. Agatonovic-Kustrin S, Beresford R (2000) Basic concepts of artificial neural network (ANN)
modeling and its application in pharmaceutical research. J Pharm Biomed Anal 22(5):717–727.
https://doi.org/10.1016/s0731-7085(99)00272-1
21. Bergstra A, Brunekreef B, Burdorf A (2018) The effect of industry-related air pollution on
lung function and respiratory symptoms in school children. Environ Health A Global Access
Sci Source 17:30. https://doi.org/10.1186/s12940-018-0373-2
22. Sinnott RO, Guan Z (2018) Prediction of air pollution through machine learning approaches on
the cloud. In: 2018 IEEE/ACM 5th international conference on big data computing applications
and technologies (BDCAT). Zurich, pp 51–60. https://doi.org/10.1109/BDCAT.2018.00015.
23. Bhalgat P, Bhoite S, Pitare S (2019) Air quality prediction using machine learning algorithms.
Int J Comput Appl Technol Res 8. https://doi.org/10.7753/IJCATR0809.1006
24. Carbajal-Hernández JJ (2012) Assessment and prediction of air quality using fuzzy logic and
autoregressive models. Atmos Environ 60:37–50
25. Nallakaruppan MK, SurejIlango H (2017) Location aware climate sensing and real time data
analysis. In: 2017 world congress on computing and communication technologies (WCCCT).
IEEE
26. Li Y, Chen Q, Zhao H, Wang L, Tao R (2015) Variations in pm10, pm2.5 and pm1.0 in an urban
area of the Sichuan basin and their relation to meteorological factors. Atmosphere 6(1):150–163
27. Mahajan S, Chen L-J, Tsai T-C (2017) An empirical study of PM2.5 forecasting using neural
network. In: IEEE smart world congress, At San Francisco, USA
28. Franklin BA, Brook R, Pope CA (2015) Air pollution and cardiovascular disease. Curr Prob
Cardiol 40(5):207–238. ISSN 0146-2806
29. Bansal M, Aggarwal A, Verma T, Sood A (2019) Air quality index prediction of Delhi using
LSTM. https://doi.org/10.13140/RG.2.2.26885.70884
30. Chang Y-S, Chiao H-T, Abimannan S, Huang Y-P, Tsai Y-T, Lin K-M (2020) An LSTM-based
aggregated model for air pollution forecasting. Atmos Pollut Res 11(8):1451–1463. ISSN
1309-1042. https://doi.org/10.1016/j.apr.2020.05.015
31. Belavadi S, Rajagopal S, Ranjani R, Mohan R (2020) Air quality forecasting using LSTM
RNN and wireless sensor networks. Procedia Comput Sci 170:241–248. https://doi.org/10.
1016/j.procs.2020.03.036
32. Gul S, Khan GM (2020) Forecasting hazard level of air pollutants using LSTM’s. In: Maglogiannis I, Iliadis L, Pimenidis E (eds) Artificial intelligence applications and innovations. AIAI
2020. IFIP advances in information and communication technology, vol 584. Springer, Cham.
https://doi.org/10.1007/978-3-030-49186-4_13
33. Jiao Y, Wang Z, Zhang Y (2019) Prediction of air quality index based on LSTM. In: 2019 IEEE
8th joint international information technology and artificial intelligence conference (ITAIC).
Chongqing, China, pp 17–20. https://doi.org/10.1109/ITAIC.2019.8785602
34. Chaudhary V, Deshbhratar A, Kumar V, Paul D, Samsung (2018) Time series based LSTM
model to predict air pollutant’s concentration for prominent cities in India
35. Kumar A, Goyal P (2013) Forecasting of air quality index in Delhi using neural network based
on principal component analysis. Pure Appl Geophys 170:711–722. https://doi.org/10.1007/
s00024-012-0583-4
36. Chatterjee A, Mukherjee S (2020) The impact of lockdown on GDP growth & COVID-19
spread: insights from a mathematical simulation exercise for India