From: Rainfall modeling using two different neural networks improved by metaheuristic algorithms
Input | PC1 | PC2 | PC3 | PC4 | PC5 |
---|---|---|---|---|---|
R (t–1) | 0.93 | 0.90 | 0.87 | 0.84 | 0.82 |
R (t–2) | 0.89 | 0.86 | 0.83 | 0.81 | 0.80 |
R (t–3) | 0.87 | 0.84 | 0.82 | 0.78 | 0.77 |
R (t–4) | 0.83 | 0.82 | 0.81 | 0.76 | 0.75 |
R (t–5) | 0.81 | 0.80 | 0.78 | 0.75 | 0.72 |
R (t–6) | 0.72 | 0.70 | 0.72 | 0.71 | 0.70 |
R (t–7) | 0.65 | 0.64 | 0.63 | 0.60 | 0.58 |
R (t–8) | 0.61 | 0.60 | 0.59 | 0.57 | 0.55 |
R (t–9) | 0.60 | 0.58 | 0.55 | 0.52 | 0.50 |