Design of Neuro-Fuzzy based inferential measurement of stripper unit in a fertilizer plant
Yul Yunazwin Nazaruddin, Ilham R. Hakim, Tua A. Tamba, Satriyo Nugroho · 2016
This paper proposes an alternative solution to overcome the difficulties in measuring the primary variable of a stripper unit in a fertilizer plant using Adaptive Neuro-Fuzzy Inference System (ANFIS) technique. Inferential measurement is a method to predict the value of the primary variable of the model generated by the input-output relationships of the process affecting the primary variable the process. Using the real-time operational data collected from stripper unit of the fertilizer plant, the technique was able to estimate the value of the primary variable (benfield solution) with error criteria (RMSE value) of 0.467 in the learning stage, and 0.447 at the validation stage.