传感技术学报Issue(12)：1649-1654,6.DOI:10.3969/j.issn.1004-1699.2013.12.005
基于动态分类器集成的MEMS气体传感器阵列的气体定性识别方法
A Method for Gas Qualitative Discrimination Using MEMS Gas Sensor Array Based on Dynamic Classifier Ensemble
摘要
Abstract
Sensor response drift remains to be the most challenging problem in gas sensing. We proposed a novel ensemble method with dynamic weights to solve the gas discrimination problem regardless of their concentration with high accuracy over extended periods of time. The method uses a dynamic weighted combination of classifiers trained at different points of time. Their weights in testing future datasets are predicted by fitting functions which are obtained by proper fitting of optimal weights in training. We compared the performances of the proposed method and competing methods in experiment based on the public dataset over a period of three years. As results illustrate,the proposed method performs better than others. Furthermore,the method can be further optimized by applying a fitting function that is better match variation of the optimal weight over time.关键词
MEMS气体传感器/传感器阵列/漂移补偿/分类器集成/动态加权Key words
MEMS gas sensor/sensor array/drift compensation/classifier ensemble/dynamic weights分类
信息技术与安全科学引用本文复制引用
刘航,唐祯安..基于动态分类器集成的MEMS气体传感器阵列的气体定性识别方法[J].传感技术学报,2013,(12):1649-1654,6.基金项目
国家自然科学基金项目(61131004) （61131004）
中央高校基本科研业务费专项资金项目(DUT11RC(3)74) （DUT11RC(3）
