区间极限学习机结合遗传算法用于红外光谱气体浓度反演的研究

提出一种新的有效的FTIR光谱气体浓度反演的方法。 该方法将区间划分的思想用于红外光谱波长优化筛选，即将红外光谱在给定波长范围内划分为若干个子区间，在每个子区间中利用遗传算法(genetic algorithm, GA)优化后的极限学习机(extreme learning machine，ELM)建立浓度预测模型，根据每个子区间测试集均方根误差RMSE和相关系数R2的大小评价模型的泛化性能，筛选出最优子区间组合建立预测模型。 通过含干扰组分(CO₂，N₂O)的CO气体的 FTIR光谱对提出的算法进行了验证，在波段为2 140～2 220 cm-1范围内利用区间法筛选出的最优组合作为变量，应用GA-ELM建立的浓度反演模型，其决定系数R2为0.987 4，均方根误差RMSE为154.996 3，建模时间仅为0.8 s，表明该算法(Interval-GA-ELM, iGELM)的应用不仅缩短了建模时间，而且在干扰组分存在的情况下，依然可以准确筛选出特征波长，从而提高了模型稳定性和预测精度，为大气污染气体遥测分析提供了行之有效的方法。

Research on Concentration Retrieval of Gas FTIR Spectra by Interval Extreme Learning Machine and Genetic Algorithm

This paper proposed a novel effective quantitative analysis method for FTIR spectroscopy of polluted gases, which select the best wavenumbers based on the idea of interval dividing. Meanwhile, genetic algorithm was adopted to optimize the connect weights and thresholds of the input layer and the hidden layer of extreme learning machine (ELM) because of its global search ability. Firstly, the whole spectrum region was divided into several subintervals; Secondly, the quantitative analysis model was established in each subinterval by using optimized GA-ELM; Thirdly, the best combination of subintervals was selected according to the generalized performance of each subinterval model by computing the parameters root mean square error (RMSE) and determined coefficients r. In this paper, the mixture of CO, CO₂ and N₂O gases were selected as the research object and the whole spectrum range was from 2 140 to 2 220 cm-1. The experiment results showed that the RMSE of model established with the selected wavenumbers was 154.996 3, the corresponding r can reach 0.987 4, and the running time was just 0.8 seconds, which indicated that the concentration retrieval model established with the proposed Interval-GA-ELM (iGELM) method can not only reduce the modeling time, but also can improve the stability and predict accuracy, especially under the condition of the exist of interferents, which providing an effective approach to the remote analysis of polluted gases.