Team:Groningen/Modelling/22 August 2013
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<p>Today we implemented the simulated annealing algorithm for approximating the chemotaxis parameters. It failed horribly. </p> | <p>Today we implemented the simulated annealing algorithm for approximating the chemotaxis parameters. It failed horribly. </p> | ||
<p>As an error function we used the distance between TM0, TD0, VP and AP concentrations when 0 attractant and 10 micro mol attractant was present, the maximum value of YP with 10 attractant present, and the distance between YP values when 0 attractant and 10 attractant was present. It strived to maximize YP with 10 micromol present, minimize the distance between YP equillibria values with 0 and 10 micro mol present, and to maximize the distance between AP, VP, TD0 and TM0 equillibria values with 0 and 10 micromol present. </p> | <p>As an error function we used the distance between TM0, TD0, VP and AP concentrations when 0 attractant and 10 micro mol attractant was present, the maximum value of YP with 10 attractant present, and the distance between YP values when 0 attractant and 10 attractant was present. It strived to maximize YP with 10 micromol present, minimize the distance between YP equillibria values with 0 and 10 micro mol present, and to maximize the distance between AP, VP, TD0 and TM0 equillibria values with 0 and 10 micromol present. </p> |
Revision as of 12:45, 23 August 2013
Mike
Today we implemented the simulated annealing algorithm for approximating the chemotaxis parameters. It failed horribly.
As an error function we used the distance between TM0, TD0, VP and AP concentrations when 0 attractant and 10 micro mol attractant was present, the maximum value of YP with 10 attractant present, and the distance between YP values when 0 attractant and 10 attractant was present. It strived to maximize YP with 10 micromol present, minimize the distance between YP equillibria values with 0 and 10 micro mol present, and to maximize the distance between AP, VP, TD0 and TM0 equillibria values with 0 and 10 micromol present.
We expect it failed because of the sensitivity of the model, the sheer volume of the search space, and variables in the error function that, to some extent, strive to contradict one another. Tomorrow we will try again.