Genetic algorithm optimization of computing-modeli
2016-08-23
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In real life, real hard question to described by a linear model. Neural networks appear, greatly reduces the difficulty of modeling and effort. Let us simply neural network as a black box, based on input and output data, learning of neural network according to the relevant rules, can the establishment of mathematical model for describing the problem. However, when the mathematical model of the input variables (factors) when many, between the chosen independent variables are not independent of each other, using neural networks prone to overfitting, which led to the model presented by issues such as low, modeling for a long time. Therefore, until the model is established, there is necessary to optimize the input variable selection, will get rid of redundant arguments, select best reflects the input-output relationships of the variables involved in modeling. Commonly used methods are the principal components analysis and partial least squares, the case try using genetic algorithm optimiza
matlab
算法
遗传
优化
计算
建模
自变量
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