Data fusion method for gas sensor array

The invention discloses a data fusion method for a gas sensor array. A traditional atom search algorithm is improved by adopting a dynamic self-adaptive position updating coefficient and Gaussian mutation operation; seven standard test functions are used to carry out optimization performance test on the improved atom search algorithm; finally, the minimum value of the test function can be found. In addition, in all the seven test functions, the sum of the precision and the convergence rate of the algorithm is superior to those of FOA, PSO and GA algorithms, the algorithm is applied to a generalized average algorithm of gas sensor array data fusion, and the result shows that a satisfactory gas sensor array data fusion result can be successfully obtained by applying the method. 本发明公开了一种气体传感器阵列数据融合方法，采用动态自适应位置更新系数和高斯变异操作对传统的原子搜索算法进行改进，利用7个标准测试函数对改进后原子搜索算法进行寻优性能测试，最终能够找到测试函数的最小值，而且在所有的7个测试函数中，本算法的精度和收敛速度和均优于FOA、PSO和GA算法，将本算法运用到气体传感器阵列数据融合的广义平均算法中，结果表明，运用该方法能够成功获得满意的气体传感器阵列数据融合结果。