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Method of Binary Analytic Programming to Look for Optimal Mathematical Expression

机译:寻找最佳数学表达式的二元分析编程方法

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In the known methods of symbolical regression by search of the solution with the help of a genetic algorithm, there is a problem of crossover. Genetic programming performs a crossover only in certain points. Grammatical evolution often corrects a code after a crossover. Other methods of symbolical regression use excess elements in a code for elimination of this shortcoming. The work presents a new method of symbolic regression on base of binary computing trees. The method has no problems with a crossover. Method use a coding in the form of a set of integer numbers like analytic programming. The work describes the new method and some examples of codding for mathematical expressions.
机译:在已知的借助遗传算法搜索解的符号回归方法中,存在交叉的问题。遗传编程仅在某些点执行交叉。语法演变通常会在交叉后纠正代码。符号回归的其他方法使用代码中的多余元素来消除此缺点。这项工作提出了一种基于二进制计算树的符号回归的新方法。该方法在交叉方面没有问题。该方法使用一组整数形式的编码,如解析编程。该作品描述了这种新方法以及一些数学表达式的编码示例。

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