Page 29 - Emerging Trends and Innovations in Web-Based Applications and Technologies

International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
Statement Architecture

ACKNOWLEDGEMENT particularly for optimizing crop selection. The proposed
I sincerely express my gratitude to Prof. Shweta Wase and system employs K-Means Clustering to categorize areas
Prof. Poonam Kale for their invaluable guidance and based on crucial environmental parameters like soil
support in completing my Crop Recommendation System composition, pH, temperature, and precipitation. Using
project. I also extend my thanks to Prof. Anupam Chaube, machine learning models, the system provides accurate,
Head of the Computer Department, for their insightful data-driven crop suggestions, enabling farmers to make
advice and encouragement. Additionally, I appreciate the more informed choices. The results suggest that clustering-
cooperation and assistance of all faculty members and non- based approaches substantially enhance precision
teaching staff of the Science and Technology Department, agriculture by reducing uncertainties and boosting
whose support played a crucial role in completing this agricultural yields. Additionally, the web-based platform
project. Their collective efforts and guidance have been ensures that farmers can easily access real-time crop
instrumental in making this endeavor successful. recommendations tailored to their specific geographic
locations. This investigation highlights the transformative
Conclusion
effect of machine learning on agricultural decision-making
This study emphasizes the importance of machine learning processes. Future studies should consider incorporating
and clustering methods in contemporary agriculture,

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