Improved data clustering methods and integrated A-FP algorithm for crop yield prediction

Author:

Vani P. Suvitha,Rathi S.

Publisher

Springer Science and Business Media LLC

Subject

Information Systems and Management,Hardware and Architecture,Information Systems,Software

Reference23 articles.

1. Khaki, S., Wang, L.: Crop yield prediction using deep neural networks. Front. Plant Sci. 10(621), 1–10 (2019)

2. Bose, P., Kasabov, N.K., Bruzzone, L., Hartono, R.N.: Spiking neural networks for crop yield estimation based on spatiotemporal analysis of image time series. IEEE Trans. Geosci. Remote Sens. 54(11), 6563–6573 (2016)

3. Mateo-Sanchis, A., Piles, M., Muñoz-Marí, J., Adsuara, J.E., Camps-Valls, G.: Synergistic integration of optical and microwave satellite data for crop yield estimation. Remote Sens. Environ. 234, 1–12 (2019)

4. Narkhede, U.P., Adhiya, K.P.: Evaluation of modified K-means clustering algorithm in crop prediction. Int. J. Adv. Comput. Res. 4(16), 709–807 (2014)

5. Parthasarathy, P., Vivekanandan, S.: A typical IoT architecture-based regular monitoring of arthritis disease using time wrapping algorithm. Int. J. Comput. Appl. 42(3), 222–232 (2020)

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