To Analyse the Impact of Water Scarcity in Developing Countries Using Machine Learning-Reference-Cited by-同舟云学术

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To Analyse the Impact of Water Scarcity in Developing Countries Using Machine Learning

Published:2022 Issue: Volume: Page:53-63
ISSN:2190-3018
Container-title:Evolution in Computational Intelligence
language:
Short-container-title:

Author:

Raj Kiran S.,Kumar Priyanka

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-6616-2_6

Reference10 articles.

1. Dhanush, G.A., Raj, K.S., Kumar, P.: Blockchain aided predictive time series analysis in supply chain system. In: Mekhilef, S., Favorskaya, M., Pandey, R.K., Shaw, R.N. (eds.) Innovations in Electrical and Electronic Engineering, pp. 913–925. Springer, Singapore (2021)

2. Mittal, S., Mittal, M., Khan, M.S.A.: Ground-Level Water Predication Using Time Series Statistical Model, pp. 427–437 (2021). https://doi.org/10.1007/978-981-15-5421-6_43

3. Moleda, M., Momot, A., Mrozek, D.: Predictive maintenance of boiler feed water pumps using scada data. Sensors 20(2) (2020). https://doi.org/10.3390/s20020571, https://www.mdpi.com/1424-8220/20/2/571

4. Pandey, S., Muthuraman, S., Shrivastava, A.: Data Classification Using Machine Learning Approach, pp. 112–122 (2018). https://doi.org/10.1007/978-3-319-68385-0_10

5. Qin, T.L., Yan, D.H., Wang, G., Yin, J.: Water demand forecast in the baiyangdian basin with the extensive and low-carbon economic modes. J. Appl. Math. 2014, 673485 (2014)

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