PSO and NN modeling for photocatalytic removal of pollution in wastewater

Razvarz S., Jafari R., Yu W., Khalili Golmankhaneh A.

14th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2017, Mexico City, Meksika, 20 - 22 Eylül 2017, (Tam Metin Bildiri) identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/iceee.2017.8108825
  • Basıldığı Şehir: Mexico City
  • Basıldığı Ülke: Meksika
  • Van Yüzüncü Yıl Üniversitesi Adresli: Evet

Özet

This paper discusses the elimination of C.I. Acid Yellow 23 (AY23) using UV/Ag-TiO2 process. To anticipate the photocatalytic elimination of AY23 with the existence of Ag-TiO2 nanoparticles processed under desired circumstances, two computational techniques namely neural network (NN) and particle swarm optimization (PSO) modeling are developed. A summed up of 100 data are used to establish the models, wherein introductory concentration of dye, UV light intensity, initial dosage of nano Ag-TiO2 and irradiation time are the four parameters applied as the input variables and elimination of AY23 as output variable. The comparison of the predicted results by designed models and the experimental data proves that the performance of the NN model is comparatively sophisticated than the PSO model.