Table 1. Comparison of residual scores and parameter estimates obtained from pLSA and eSS optimisation approaches.
KrLSA | KreSS | KniLSA | KnieSS | GtLSA | GteSS | |
WLS | 487.67 | 487.62 | 1960.10 | 1958.20 | 868.15 | 865.05 |
RMS | 11.21 | 11.10 | 21.13 | 21.20 | 17.23 | 17.19 |
α | 0.0970 | 0.0964 | 0.0783 | 0.0785 | 0.1107 | 0.1139 |
λ | 0.0764 | 0.0756 | 0.0770 | 0.0772 | 0.1110 | 0.1139 |
D | 0.0015 | 0.0015 | 0.0125 | 0.0126 | 0.0159 | 0.0180 |
τ | 5.2953 | 5.1786 | 6.3083 | 6.3649 | 2.3900 | 2.6127 |
Scores and parameter estimates from two representative solutions (one for each optimisation method) are shown for Kr, kni, and gt models. WLS corresponds to the weighted least squares score as defined in equation 2. RMS is the root-mean-square score as defined in equation 3. is the production rate, the decay rate, the diffusion rate, and the production delay as defined in equation 1. LSA indicates scores and estimates from Lam Simulated Annealing, eSS scores and estimates from enhanced scatter search.