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

Analysis of Seepage Induced Soil Mass Movements and Stabilization using Vertical Sand Drains
Analysis of Seepage Induced Soil Mass Movements and Stabilization using Vertical Sand Drains
Study on Rural Water Management & Usage
Study on Rural Water Management & Usage
Coastal reservoir concept to impound Netravati River flood waters: A sustainable strategy for water resource development for Mangalore and Bangalore
Coastal reservoir concept to impound Netravati River flood waters: A sustainable strategy for water resource development for Mangalore and Bangalore
Virtual Amrita Laboratories in Biotechnology
Virtual Amrita Laboratories in Biotechnology
Cooperative MIMO in Wireless Sensor Network for Precision Agriculture
Cooperative MIMO in Wireless Sensor Network for Precision Agriculture
Admissions Apply Now