Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{177912,
        author = {Sibbala Chandana and Gabburi Neha and Civini Meghana and Pathakamuri Harshitha and Mr. Praveen Giridhar Pawaskar},
        title = {AI-Based Crop Recommendation with Weather Prediction using Data Mining},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {2553-2556},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=177912},
        abstract = {Weather forecasting is a method to predict what the atmosphere will be like in a particular place by using scientific knowledge to make weather observations. Weather forecasting is a challenging task due to the dynamic and complex nature of atmospheric conditions. Recently, data mining techniques have been applied to predict weather patterns using machine learning algorithms.
The study demonstrates that data mining techniques can be used to predict weather patterns accurately and, when combined with AI models like Gemini, can serve as a comprehensive decision-support tool in precision agriculture. The proposed model can be further enhanced by incorporating additional weather variables such as cloud cover and solar radiation, as well as by exploring more sophisticated machine learning techniques like ensemble methods.},
        keywords = {User-Friendly Interface, Weather Classification, Machine Learning Algorithms, Deep Learning (CNN), Data Processing Pipeline, Pre-Processing, Model Building, Performance Metrics, AI-Powered Crop Recommendation, Climatic Conditions, Data-Driven Decision Making.},
        month = {May},
        }