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基于GSA的厌氧发酵原料碳氮比NIRS快速检测
Authors
刘金明
孙勇
+4 more
李文哲
甄峰
程秋爽
许永花
Publication date
1 January 2019
Publisher
Abstract
在以预处理后玉米秸秆、秸秆粪便混合物为原料进行厌氧发酵生产沼气时,为了对厌氧发酵原料碳氮比进行快速检测,将近红外光谱(NIRS)与偏最小二乘(PLS)回归相结合构建快速检测模型,并基于遗传模拟退火算法(GSA)构建遗传模拟退火区间偏最小二乘算法(GSA-iPLS)和双重遗传模拟退火偏最小二乘算法(DGSA-PLS)分别用于特征谱区优选和特征波长点优选,以提高回归模型的检测精度和效率。全谱1 844个波长点经GSA-iPLS进行谱区优选后,得到641个波长变量,再经DGSA-PLS进行特征波长点优选后,得到628个波长变量。DGSA-PLS回归模型验证集的决定系数(Rp^2)为0. 920,预测均方根误差为7. 178,相对分析误差为3. 805。与全谱建模相比,DGSAPLS模型的RMSEP减小了15. 87%。通过波长优选,参与建模的波长点数量显著减少,有效降低了变量维度和模型复杂度,提升了预测精度和预测能力。本文通过优选碳氮比的敏感波长变量,有效提高了预测模型的鲁棒性,为直接、快速、准确测量厌氧发酵原料的碳氮比提供了新途径
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Institutional Repository of GuangZhou Institute of Energy Conversion, CAS
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oai:ir.giec.ac.cn:344007/34342
Last time updated on 04/12/2021
Institutional Repository of GuangZhou Institute of Energy Conversion, CAS
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:ir.giec.ac.cn:344007/34344
Last time updated on 04/12/2021