Abstract
In this study, a neuroevolution algorithm has been developed for predicting various diseases in plants. The machine learning algorithms support different classification techniques that can be demonstrated for the performance improvement in plant disease prediction. Prediction of the disease depends on the weather factors which have a relationship with climate change data, the soil of that area. Here we have illustrated an approach of implementing the neuroevolution model based on ANN for predicting various plant diseases. Multiple causes and the type of illness that can affect different plants during the different seasons are predicted. Therefore the result of the proposed model assists in decision making in advance in precaution taking in a disease that may affect the plant. The results are utilized for making an advanced decision for disease avoidance in plants as well as various farm activities throughout multiple-stage it also uses the same model that can be utilized for predicting various agricultural data such as yield prediction and weather prediction.
Sign-in/Register to access full text options 
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 callDisclaimer: 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.
