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parameter_optimization [2021/08/20 13:59]
mina
parameter_optimization [2022/12/29 17:47] (current)
mina
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 ===== Selecting optimization parameters ===== ===== Selecting optimization parameters =====
  
-In the first page of the optimization wizard one has to choose which parameters one wants to find out. The list shows all parameters in the [[Active_project|current project]]. Select parameters in the list and click the **Add** button to include them in the optimization.+In the first page of the optimization wizard one has to choose which parameters one wants to find out. The list shows all parameters in the [[Projects_window#Active_project|current project]]. Select parameters in the list and click the **Add** button to include them in the optimization.
  
 For each selected parameter one has to give an initial condition, this is the starting guess in the optimization algorithm. One also has the possibility to add constraints on upper and lower bounds for each selected parameter. Default values are infinity and negative infinity respectively on these bounds, therefore there won’t be any bounds. For each selected parameter one has to give an initial condition, this is the starting guess in the optimization algorithm. One also has the possibility to add constraints on upper and lower bounds for each selected parameter. Default values are infinity and negative infinity respectively on these bounds, therefore there won’t be any bounds.
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   * **Maximum number of function evaluations allowed** - //default: 200 times number of parameters//   * **Maximum number of function evaluations allowed** - //default: 200 times number of parameters//
   * **Maximum number of iterations allowed** //default: 200 times number of parameters//   * **Maximum number of iterations allowed** //default: 200 times number of parameters//
-  * **Objective function which we want to minimize** (not editable)+  * **Objective function which we want to minimize** (not editable) - It is used for evaluating the goodness of fit of the optimization – the lower the value of this function, the better is the fit. It is calculated for each iteration and iterations are continued if the objective function is getting lower values, until the termination tolerance is reached or the user-specified maximum number of simulations is reached
  
 [1] Lagarias, J.C., J. A. Reeds, M. H. Wright, and P. E. Wright, "Convergence Properties of the Nelder-Mead Simplex Method in Low Dimensions," _SIAM Journal of Optimization_, Vol. 9 Number 1, pp. 112-147, 1998. [1] Lagarias, J.C., J. A. Reeds, M. H. Wright, and P. E. Wright, "Convergence Properties of the Nelder-Mead Simplex Method in Low Dimensions," _SIAM Journal of Optimization_, Vol. 9 Number 1, pp. 112-147, 1998.
parameter_optimization.1629460743.txt.gz · Last modified: 2021/08/20 13:59 by mina