Advancing Crop Recommendation Systems Through Ensemble Learning Techniques
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-54376-0_4
Reference21 articles.
1. Hosseinzadeh, M., Samadi Foroushani, M., Sadraei, R.: Dynamic performance development of entrepreneurial ecosystem in the agricultural sector. Br. Food J. 124, 2361–2395 (2022)
2. Mancer, M., Terrissa, L., Ayad, S., Laouz, H.: A Blockchain-based approach to securing data in smart agriculture. In: 2022 International Symposium on Innovative Informatics of Biskra (ISNIB), pp. 1–5 (2022)
3. Abbasi, R., Martinez, P., Ahmad, R.: The digitization of agricultural industry-a systematic literature review on agriculture 4.0. Smart Agric. Technol. 2, 100042 (2022)
4. Mathew, J., Joy, A., Sasi, D., Jiji, J., John, J.: Crop prediction and plant disease detection using IoT and machine learning. In: 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI), pp. 560–565 (2022)
5. Mancer, M., et al.: Blockchain technology for secure shared medical data. In: 2022 International Arab Conference on Information Technology (ACIT), pp. 1–6 (2022)
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