derivative_free_optimization
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| ====== Derivative Free Optimization ====== | ====== Derivative Free Optimization ====== | ||
| - | http://en.wikipedia.org/wiki/Pattern_search_(optimization) | + | -http://en.wikipedia.org/wiki/Pattern_search_(optimization) |
| - | http://en.wikipedia.org/wiki/Random_search | + | -http://en.wikipedia.org/wiki/Random_search |
| - | http://en.wikipedia.org/wiki/Nelder%E2%80%93Mead_method (Ameba) | + | -http://en.wikipedia.org/wiki/Nelder%E2%80%93Mead_method (Ameba) |
| Pattern search je relativne rychly protoze sampluje pouze vyznacne smery. Minimalne sampluje 1 smer, maximalne 2N. Pamatuje si predchozi smer takze se pohybuje effektivne. | Pattern search je relativne rychly protoze sampluje pouze vyznacne smery. Minimalne sampluje 1 smer, maximalne 2N. Pamatuje si predchozi smer takze se pohybuje effektivne. | ||
| problem nastava v okamziku kdy se objevi uzke udoli sikme na hlavni osy. V tom pripade Pattern_search sice konverguje ale s velice kratkym krokem (aby se vlez do sirky udoli) coz vede k velkemu poctu potrebnych iteraci. | problem nastava v okamziku kdy se objevi uzke udoli sikme na hlavni osy. V tom pripade Pattern_search sice konverguje ale s velice kratkym krokem (aby se vlez do sirky udoli) coz vede k velkemu poctu potrebnych iteraci. | ||
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| + | Resenim je pouzit znalosti okolnich bodu k odhadu gradientu, pripadne i stredu paraboly. | ||
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| + | === algoritmus === | ||
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| + | == Pattern run == | ||
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derivative_free_optimization.txt · Last modified: 2012/05/24 09:59 (external edit)
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