Propose and implement a Rule-Based System to Predict Crop Yield Production

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Published: Mar 1, 2024
DOI: https://doi.org/10.29070/bs9vmv33
Keywords:
Predict, Crop, Yield, Production and Climate

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Authors

Pramod Kumar Dwivedi

Research Scholar, Awadhesh Pratap Singh University, Rewa, Madhya Pradesh, India

Dr. Prabhat Pandey

Professor, Department of Computer Science, Awadhesh Pratap Singh University, Rewa, Madhya Pradesh, India

Abstract

Accurate meteorological forecasting plays a pivotal role in agricultural decision-making, particularly in determining crop yield potential and optimizing agricultural practices. This study investigates the application of data mining techniques in meteorological forecasting to enhance crop yield prediction accuracy Preliminary findings suggest that data mining techniques, including machine learning algorithms, neural networks, and ensemble methods, offer significant potential for improving the accuracy and reliability of meteorological forecasts for crop yield prediction. In conclusion, this study underscores the potential of data mining techniques in improving meteorological forecasting for crop yield potential assessment.

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Issue

Vol. 21 No. 1 (2024): Journal of Advances in Science and Technology (JAST)

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