Machine learning for Food grains price prediction

arasu b

arasu b

Bengaluru, Karnataka

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  • 0 Collaborators

Volatile and rising agricultural process put a significant effect on the fight against poverty all over the world. An accurate pricing of the future food could be a vital planning tool for various farmers across the globe. It is a predominant, that developing countries are heavily dependent on the export/import of food grains. But, unfortunately, the food grains prices would drop creating a substantial loss to the farmers. The main purpose of this research is to allow producers keep informed and aid them for a better decision and to manage price risk. Artificial Intelligence plays a vital role in the prediction analysis especially the machine learning algorithms.Currently we are testing the algorithm with the data sets available, and the initial results are encouraging. Our aim is to ensure fine tune the algorithm to match the historical price and the predicted price. We are planning to consider other factors like weather, local issues, that contributes to the price fluctuations. Our contribution lies in the area of modifying the machine learning techniques that could be used with the H20. If the price prediction could be used correctly, farmers could be informed to avoid the cultivation of that product and switch for a different crop. This way, it increases the economy, gives a better control for farmers and saving them from being bankrupt. ...learn more

Project status: Concept

Artificial Intelligence

Intel Technologies
Other

Overview / Usage

An accurate pricing of the future food could be a vital planning tool for
various farmers across the globe. It is a predominant, that developing countries are heavily
dependent on the export/import of food grains. But, unfortunately, the food grains prices
would drop creating a substantial loss to the farmers. The main purpose of this research is to
allow producers keep informed and aid them for a better decision and to manage price risk.

Methodology / Approach

contribution lies in the area of modifying the machine learning techniques that could be used
with the H20. If the price prediction could be used correctly, farmers could be informed to
avoid the cultivation of that product and switch for a different crop. This way, it increases the
economy, gives a better control for farmers and saving them from being bankrupt.

Technologies Used

Intel Py, H2O, ML Libs

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