Статья

Soil pH Prediction using Artificial Intelligence

Sandeep Kumar SunoriDepartment of ECE, Graphic Era Hill University, Bhimtal Campus Bhimtal, IndiaJanmejay PantSchool of Computing, Graphic Era Hill University, Bhimtal Campus Bhimtal, IndiaAjay Kumar YadavIshan Y PandyaKamal AlaskarDepartment of Computer Application, Bharti Vidyapeeth (Deemed to be University), Kolhapur, Maharastra, IndiaN. ThangaduraiDepartment of Electronics and Communication Engineering, JAIN (Deemed-to-be University), Bangalore, IndiaSudhanshu MauryaSchool of Computing, Graphic Era Hill University, Bhimtal Campus, Uttarakhand, India

2021en

ABI

Аннотация

The pH value of soil is a critical parameter which governs the fertility of soil. In Uttarakhand, due to very encouraging climatic conditions like temperature, moisture and humidity, the soil has an appropriate pH value, and hence it is very fertile, due to which, the agriculture has become a significant source of income for Uttarakhand people. This research article is based upon the secondary data pertaining to soil of Kumaun region of Uttarakhand. This available data has been used to develop and train RBF NN (radial basis function neural network) and FIS (subtractive clustering based fuzzy inference system), on MATLAB, for predicting the pH of soil out of the given minerals concentration e.g. P, K, Fe, Mn, Cu. Eventually, the prediction performance of both the designed models are compared in terms of mean square prediction error.

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Идентификаторы

DOI: 10.1109/gcat52182.2021.9587755

Цитирования и источники

Цитирований: 2Использованных источников: 0

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