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S c E-U a algorithm
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SCE-UA is a global optimization algorithms, it integrates the random search algorithm and simplex method, cluster analysis and biological evolutionary advantage, able to deal effectively with the target function to reflect existing crude, insensitive and not raised issues such as, and not local minima Interference. The basic idea is based on the certainty of compound search technology and principle of biological evolution in nature combined for the competition in its key segment hybrid evolutionary algorithm (CCE). In CCE, each compound's vertices are potential fathers, groups are likely to contribute to the next generation of computing. Each compound acts like a pair of parents. Selected at random were applied in the construction of composite, making search more thoroughly in the feasible region. The code using the SCE-UA algorithm for automatic calibration of vertical mixed flow parameters, and can solve problems in the calibration.
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Simplex method for objective optimization of xinan
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1953 United States mathematician G.B. Danzig for improved simplex method of accumulated rounding errors in each iteration, modified simplex method is proposed. Roughly the same basic steps, and the simplex method, the main difference is in the successive iterations no longer based on Gaussian elimination, but directly by the inverse of the old array to new array to calculate the inverse, and then determine the number of tests. Doing so can reduce the accumulated error iterations, improves the accuracy, but also reduces the storage on your computer. Optimum seeking method in mathematics is to find a faster more accurate calculation method of extreme value of function. 1953 United States mathematician j. Kiefer made a single factor and 0.618 optimization which fraction method (also known as the Golden law), later parabola method is proposed. As for two-factor and multi-factor optimization method, it involves more complicated issues, methods and ideas are more commonly u
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