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

Amrita Virtual Interactive E-Learning World (A-VIEW)
Amrita Virtual Interactive E-Learning World (A-VIEW)
Development & Prototyping of ICT enabled Smart Charging Network Components
Development & Prototyping of ICT enabled Smart Charging Network Components
Integrative Health and Wellbeing – Strengthening Tribal Health with Preventative Care and Awareness
Integrative Health and Wellbeing – Strengthening Tribal Health with Preventative Care and Awareness
Cerebellum Inspired Approach for Pattern Classification in Robots
Cerebellum Inspired Approach for Pattern Classification in Robots
Cow-kin: Smart and Precision Animal Farming for the Health and Welfare of the Cattle
Cow-kin: Smart and Precision Animal Farming for the Health and Welfare of the Cattle
Admissions Apply Now