Figures index

From

Using Artificial Neural Network to Model Water Discharge and Chemistry in a River Impacted by Acid Mine Drainage

Toluwaleke Ajayi, Dina L.Lopez, Abiodun E.Ayo-Bali

American Journal of Water Resources. 2021, 9(2), 63-79 doi:10.12691/ajwr-9-2-4
  • Figure 1. Configuration and topology of ANN [22]
  • Figure 2. Schematic diagram of a typical jth node [22]
  • Figure 3. a: Map of RC watershed, showing HF subwatershed. The blue circle is the BM gage station and black circle is location of doser ; b: HF sampling points and biologic recovery zones [41]
  • Figure 4. Model BM1 output using separated values of temperature (Tempt-1 to Tempt-9) and API with k = 0.95
  • Figure 5. r values for all lowered decay factor
  • Figure 6. r-value for each variation in k values of Blaney Criddle ET method
  • Figure 7. r values of the model run using variation in decay factor of API and ATI
  • Figure 8. Model BM7 using GRNN, with the introduction of ATI
  • Figure 9. Model for HF flow using GMDH
  • Figure 10. Model of chemical concentration/load for acidity, alkalinity, and Ca
  • Figure 11. Model of chemical concentration/load for Mg, sulfate, and K