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Design and Develop a Decision-Making Assistance Model for Agriculture Product Price Prediction: Deep Learning
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Author(s): Rajeev Kudari (Koneru Lakshmaiah Education Foundation, India), Aggala Naga Jyothi (Vignan's Institute of Information Technology, India), Abdul Mannan Mohd (Mahatma Gandhi University, India)and Prabha Shreeraj Nair (S. B. Jain Institute of Technology Management and Research, India)
Copyright: 2022
Pages: 12
Source title:
Handbook of Research on Technologies and Systems for E-Collaboration During Global Crises
Source Author(s)/Editor(s): Jingyuan Zhao (University of Toronto, Canada)and V. Vinoth Kumar (Jain University, India)
DOI: 10.4018/978-1-7998-9640-1.ch018
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Abstract
Most of India's wealth and economy are derived from agriculture. Crop production price forecasting has always been a challenge for farmers. Climatological changes as well as other market variables have resulted in significant losses for farmers. Despite their best efforts, farmers are unable to sell their crops for the prices they want. A decision-assistance model for agricultural product price forecasting is being developed in this project. Farming decisions may be made using this method, which takes into consideration elements like yearly rainfall, WPI, and so on. A year's worth of forecasts are available from the technology. The system employs a machine learning regression approach known as decision tree regression.
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