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

Climate Change Impact and Self Help Adaptation Strategies in the Sunderban Region of West Bengal
Climate Change Impact and Self Help Adaptation Strategies in the Sunderban Region of West Bengal
Green Campuses
Green Campuses
An Edge-based Cyber-Physical System for Smart Polyhouse Solar Drying of Agricultural Food Products (Phase-2)
An Edge-based Cyber-Physical System for Smart Polyhouse Solar Drying of Agricultural Food Products (Phase-2)
Non-Electric Cooling Solutions for Tribal Villages
Non-Electric Cooling Solutions for Tribal Villages
Dynamic Landslide Early Warning Framework
Dynamic Landslide Early Warning Framework
Admissions Apply Now