基于基因表达式编程的传感器校正函数挖掘方法

对传感器进行非线性校正是提高其工作性能的重要环节.在分析传感器的工作特征的基础上，设计了带有正态分布兴趣度函数的适应度函数，引进了上下限函数作为工具，提出了基于基因表达式编程的用于解决传感器系统非线性校正问题的SGEP算法，并进行了校正实验，实验表明，该方法比传统方法更灵活有效.

A method for mining rectification function of sensor based on gene expression programming

The nonlinearity rectification is an important task to improving the sensor performance. This paper analyzes the sensors characteristics and designs a fitness function with interest in normal distribution and use boundary functions presents a new method named SGEP. The new method based on Gene Expression Programming is for solving the problem of the nonlinearity rectification in sensor system. The experimental result show that the new method is more effective and more flexible than traditional method.