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Team:Groningen/Modelling/21 August 2013
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Today we identified another faulty differential equation, and we implemented the simulating annealing algorithm for a dummy problem. The error function was simply the distance between some current value x and some goal y. The algorithm stabilizes around the goal as the time (or temperature) decreases, along with the degree of randomness. The plots below illustrate this for y = 1.9 and 0.4 respectively. | Today we identified another faulty differential equation, and we implemented the simulating annealing algorithm for a dummy problem. The error function was simply the distance between some current value x and some goal y. The algorithm stabilizes around the goal as the time (or temperature) decreases, along with the degree of randomness. The plots below illustrate this for y = 1.9 and 0.4 respectively. | ||
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Revision as of 13:50, 21 August 2013
Today we identified another faulty differential equation, and we implemented the simulating annealing algorithm for a dummy problem. The error function was simply the distance between some current value x and some goal y. The algorithm stabilizes around the goal as the time (or temperature) decreases, along with the degree of randomness. The plots below illustrate this for y = 1.9 and 0.4 respectively.
