AI-Enabled Analysis of Climate Change on Agriculture and Yield Prediction for Coastal Area

Author:

Manikavelan D.,Thouti Swapna,Ashok M.,Chandiraprakash N.,Rajeswaran N.

Publisher

Springer Nature Singapore

Reference14 articles.

1. Yu M, Xu FC, Hu W, Sun J, Cervone G (2021) Using long short-term memory (LSTM) and internet of things (IoT) for localized surface temperature forecasting in an urban environment. IEEE J 9:137406–137418

2. Nigam A, Garg S, Agrawal A, Agrawal P (2021) Crop yield prediction using machine learning algorithms. Int J Eng Res Technol (IJERT) 9(13):23–26

3. Meng X, Liu M, Wu Q (2020) Prediction of rice yield via stacked LSTM. Intl J Agric Environ Inform Syst 11(1):86–95

4. Moraye K, Pavate A, Nikam S, Thakkar S (2021) Crop yield prediction using random forest algorithm for major cities in Maharashtra State. Intl J Innov Res Comput Sci Technol (IJIRCST) 9(2):2347–5552

5. Hewage P, Behera A, Trovati M, Pereira E (2019) Long-short term memory for an effective short-term weather forecasting model using surface weather data. Springer, Cham

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