Deep Learning for Predictive Analytics in Indian Agriculture: A Case Study of Crop Yield Prediction
DOI:
https://doi.org/10.36676/irt.v8.i4.1508Abstract
Predictive analytics, powered by deep learning, is transforming Indian agriculture by improving crop yield prediction and resource management. This paper presents a deep learning-based model that leverages Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to predict crop yields in various Indian agro-climatic zones. By incorporating weather data, soil health information, and historical crop yield data, the model aims to provide farmers with accurate, timely insights for better decision-making. The study also highlights the challenges of data collection in rural India, the need for region-specific models, and the socio-economic benefits of AI-driven agricultural solutions.
References
Vasa, Y., Mallreddy, S. R., & Jami, V. S. (2022). AUTOMATED MACHINE LEARNING FRAMEWORK USING LARGE LANGUAGE MODELS FOR FINANCIAL SECURITY IN CLOUD OBSERVABILITY. International Journal of Research and Analytical Reviews , 9(3), 183–190.
Vasa, Y., & Singirikonda, P. (2022). Proactive Cyber Threat Hunting With AI: Predictive And Preventive Strategies. International Journal of Computer Science and Mechatronics, 8(3), 30–36.
Vasa, Y., Cheemakurthi, S. K. M., & Kilaru, N. B. (2022). Deep Learning Models For Fraud Detection In Modernized Banking Systems Cloud Computing Paradigm. International Journal of Advances in Engineering and Management, 4(6), 2774–2783. https://doi.org/10.35629/5252-040627742783
Mallreddy, S. R., & Vasa, Y. (2022). Autonomous Systems In Software Engineering: Reducing Human Error In Continuous Deployment Through Robotics And AI. NVEO - Natural Volatiles & Essential Oils, 9(1), 13653–13660. https://doi.org/https://doi.org/10.53555/nveo.v11i01.5765
Vasa, Y., & Mallreddy, S. R. (2022). Biotechnological Approaches To Software Health: Applying Bioinformatics And Machine Learning To Predict And Mitigate System Failures. Natural Volatiles & Essential Oils, 9(1), 13645–13652. https://doi.org/https://doi.org/10.53555/nveo.v9i2.5764
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