SCEM
Package: | jams.components.optimizer |
Autor: | Christian Fischer |
This component performs a model calibration. It finds optimal parameter values by using the SCEM (Shuffle Complex Evolution) algorithm for optimization. (Vrugt et al., 2003) The SCEM component is similar to the SCE optimzation component. The difference is, that SCE performs a single criterion optimization and SCEM a multiple criterion optimization. In general the solution of a multiple criterion optimization problem is not a single set of parameter, but infinity many sets of parameters. This is called Pareto Front. SCEM tries to approximate the Pareto Front. For applications, the calibration - model is inserted into the context of the SCEM component. After that the parameters, their feasible range, and the optimization criterions are specified. It is possible to maximize and minimize the criterions during optimization. The process is influenzed by the number of complexes and the number of individuals in a population. A higher number of complexes and individuals increases the chance of finding optimal points, but increases computing time also. In most cases the number of complexes lies between 2 and 10 and the population-size between 5 and 50.
XML
<contextcomponent class="jams.components.optimizer.SCEM.SCEM" name="SCEM"> <var name="dirName" context="J2000g" attribute="workspaceDir"/> <var name="parameterIDs" value="Snow.ddf;Snow.t_thres;InitSoilWater.FCAdaptation;SoilWater.latVertDist;GroundWater.k"/> <var name="boundaries" value="[1.0<10.0];[-10.0<10.0];[0.0<10.0];[0.0<10.0];[1.0<10.0];"/> <var name="effMethodName" value="e2,e1,vol"/> <var name="effValue" context="J2000g" attribute="e2,e1,mse"/> <var name="MaximizeEff" value="1,1,3"/> <var name="NumberOfComplexes" value="5"/> <var name="Population" value="11"/> <var name="sampleCount" value="10000"/> [..] insert model here [..] </contextcomponent>
dirName | name of working directory | |
parameterIDs | name of parameters for optimization | |
boundaries | feasible range of every parameter | |
effMethodName | names of goodness of fit criterions | |
effValue | modelvariables of goodness of fit criterions | |
MaximizeEff | optimization mode, 1 = maximization, 4 = minimization | |
NumberOfComplexes | number of complexes | |
Population | number of individuals in population ) | |
sampleCount | maximal number of function evaluations |
Position
<model> ├─<SCE Context> │ └─<Catchment Context/> │ ├─<InitCatchmentContext/> │ ├─<InitHRUContext/> │ ├─<TemporalContext</> │ │ ├─<HRUContext/> │ │ └─<ReachContext/> │ └─<EntityOutputContext> └─</model>