Back close

An Adaptive Neuro-fuzzy Inference System to Monitor and Manage the Soil Quality to Improve Sustainable Farming in Agriculture

Project Incharge:Dr. Remya S.
An Adaptive Neuro-fuzzy Inference System to Monitor and Manage the Soil Quality to Improve Sustainable Farming in Agriculture

The hybrid neuro model is equipped with the high learning capabilities of a neural network and the reasoning ability of fuzzy logic and comes up with a model for effectively correlating the values with the target. This predictive modeling benefits a variety of stakeholders. Accurate projections can assist governments to govern themselves more efficiently.Farmer can come up with their own ideas to increase their production rate in a professional and timely manner. As a result, investors can devise more profitable and effective investment plans. This study and analysis of predictive modeling aim to anticipate the quality of agricultural data by developing a hybrid predictive technique that combines artificial neural network and optimization techniques. 

Related Projects

Tech-based Health Monitoring & Awareness
Tech-based Health Monitoring & Awareness
Brain Network Analysis from fMRI Images
Brain Network Analysis from fMRI Images
Investigating the Role of Natural Compounds in Modulating SUMOylation during Host-Pathogen Interactions
Investigating the Role of Natural Compounds in Modulating SUMOylation during Host-Pathogen Interactions
Ontology Driven Knowledge-based Systems for Disease and Treatment Prediction  
Ontology Driven Knowledge-based Systems for Disease and Treatment Prediction  
Marine Algae – An Important Source for Lectins
Marine Algae – An Important Source for Lectins
Admissions Apply Now