Extreme learning machine for solving paddy nutrient deficiencies in Davangere region
by M. Varsha; M.P. Pavan Kumar; S. Basavarajappa
International Journal of Agriculture Innovation, Technology and Globalisation (IJAITG), Vol. 3, No. 2, 2023

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.

Online publication date: Tue, 28-Nov-2023

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