Abstract
There is an growing appetite for food due to the ever increasing global population, so new technologies need to be created to increase crop yield. This paper proposes an intelligent way of forecasting crop yield and recommends the best variables for optimising crop yield. With technical developments, the emphasis has now moved to the use of computers and control systems for process management and efficiency enhancement. we estimate the crop yield per acre, in this research work to proposed hybrid approach for Chemical Fertilizer Data classification using SVM and neural network approach with expert system improvement. Yield and data obtained from Madhya Pradesh of Agriculture are used in the proposed process. Humidity, yield, temperature and rainfall are the different parameters used in the dataset.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Turkish Journal of Computer and Mathematics Education (TURCOMAT)
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
