Title: Extreme learning machine for solving paddy nutrient deficiencies in Davangere region

Authors: M. Varsha; M.P. Pavan Kumar; S. Basavarajappa

Addresses: Bapuji Institute of Engineering and Technology, Davangere, India ' Jawaharlal Nehru National College of Engineering, Shimoga, India ' G.M. Institute of Technology, Davangere, India

Abstract: Soil nutrient is an important aspect that contributes to the soil fertility and environmental effects. Traditional evaluation approaches of soil nutrient are quite hard to operate and they are very slow, making great difficulties in practical applications. The proposed study, presents extreme learning machine (ELM) for analysing the soil fertility index values of boron, zinc, organic carbon and pH in Davangere District. Boron, zinc, organic carbon, and pH concentrations in soil play significant roles in paddy crop cultivation and growth. Proposed ELM-based approach helps in the prediction of boron, zinc, organic carbon and pH index values in soil by evaluating four linear and nonlinear activations functions. Performance of ELM model is analysed by increasing the number of hidden neurons in the hidden layer.

Keywords: extreme learning machine; ELM; transfer functions; hidden neurons; back-propagation.

DOI: 10.1504/IJAITG.2023.135048

International Journal of Agriculture Innovation, Technology and Globalisation, 2023 Vol.3 No.2, pp.157 - 176

Received: 02 Sep 2022
Accepted: 17 Mar 2023
Published online: 28 Nov 2023 *