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

Chelonia Advanced Version
Chelonia Advanced Version
Treatment of Pharmaceutical and personal care products (PPCPs) using Advanced Oxidation Process
Treatment of Pharmaceutical and personal care products (PPCPs) using Advanced Oxidation Process
Development of Methodologies for Detection of Digital Contents Plagiarism
Development of Methodologies for Detection of Digital Contents Plagiarism
Comparative quantification and bioavailability assessment of Emodin in Kasamardapatra(Cassia occidentalis L. leaf) before and after addition of buttermilk using Caco2 cell lines
Comparative quantification and bioavailability assessment of Emodin in Kasamardapatra(Cassia occidentalis L. leaf) before and after addition of buttermilk using Caco2 cell lines
Development of Heterotrophic and Phototrophic Microbial Fuel Cell
Development of Heterotrophic and Phototrophic Microbial Fuel Cell
Admissions Apply Now