Abstract
In Indian economy, agriculture contributes 18% of total India GDP. A model is proposed for predicting soil series and providing suitable crop yield suggestion for that specific soil and weather. The model has been tested by applying different Deep algorithm. CNN shows highest accuracy in soil classification and suggests crops with less time. The type of soil is clay, peat, sand, humus clay. It gives us more accuracy as compared to existing system and gives more benefit to farmers. Crop prediction helps us for increasing crop production. In this paper, a low cost result given for crop.
Keywords
Crop Prediction, CNN Algorithm, python.
Citations
IRE Journals:
Vishakha Kolhe , Shivani Andure , Harshada Beldar , Rutuja Gund
"Study On: Soil Based Crop Prediction and Weather Forecasting" Iconic Research And Engineering Journals Volume 5 Issue 11 2022 Page 101-104
IEEE:
Vishakha Kolhe , Shivani Andure , Harshada Beldar , Rutuja Gund
"Study On: Soil Based Crop Prediction and Weather Forecasting" Iconic Research And Engineering Journals, 5(11)
About IRE Journals
IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
Important Links
For Authors
Volume 7:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 6:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 5:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 4:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 3:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12