Neuro-Fuzzy based Prediction of pH Value of Soil of Uttarakhand

Autor: Amit Mittal, Shweta Arora, Deepa Nainwal, Pradeep Kumar Juneja, Sudhanshu Maurya, Sandeep Kumar Sunori, Janmejay Pant
Rok vydání: 2021
Předmět:
Zdroj: 2021 5th International Conference on Trends in Electronics and Informatics (ICOEI).
DOI: 10.1109/icoei51242.2021.9452814
Popis: Uttarakhand is a northwestern state of India. It is a beautiful state, rich in flora and fauna. The 3/5 of the total area of this state is covered by rich vegetation only because of very favorable climate and quality of soil. The soil of Uttarakhand is very rich in nutrients due to an optimum pH value, and it is has an excellent fertility due to promising moisture, humidity and temperature conditions. In this state, the agriculture is the major source of income for a significant part of its total population. In this paper, the prediction of the pH value of the soil of Uttarakhand, a northern state of India, has been addressed, based on the collected secondary data of various regions of Uttarakhand. The soft computing techniques which have been adopted are Artificial Neural network (ANN) and the neurofuzzy hybrid called, Adaptive Neuro-Fuzzy Inference System (ANFIS), in MATLAB. The predictor has been designed using both the techniques, and the corresponding prediction errors are finally compared.
Databáze: OpenAIRE