Predicting the soil organic carbon by recent machine learning algorithms
Muhammad Uzair, Stefania Tomasiello, Evelin Loit, Jerry Chun Wei-Lin · 2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) · 2022
In this paper, we focus on the Soil Organic Carbon (SOC) prediction, to discuss a comparative analysis between two recently proposed techniques, namely the Adaptive Network-based Fuzzy Inference System (ANFIS) with fractional Tikhonov regularization and the Extreme Learning Machine (ELM) with the same kind of regularization. Three groups of experiments were performed using some publicly available datasets, in particular from Estonia. The results showed the good accuracy of the ANFIS-based approach.