| 摘要 |
A method of solving the inverse problem through an iterative process is provided whereby each iterative effectively solves one forward problem without having to sample the entire non-linear space. This method is a selective and iterative process for optimizing many variables that substantially achieves a global optimum solution. One particular process utilizes a neo-Darwinism method. Under this method, the sample space is iteratively analyzed via "mutations" to the value of the variable involved. Starting from a basic structure, assumed sub-optimal, we apply small variations or mutations are applied to each variable in turn, and those that are determined to improve the outcome value are kept. A better outcome value is determined to exist when a set of ratings is closer to the required set. Because the average rating is an invariant, the variable space is operated on throughout the process of looking for the combination of factors that will lead to the better outcome value.
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