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| 1 | 近红外光谱分析方法研究:从传统数据到大数据显示文摘近红外光谱分析技术作为一种绿色分析技术,在许多领域中已得到广泛应用.随着应用的深入和拓展,近红外光谱的数据类型逐渐从传统数据变成近红外光谱大数据.本文总结了近红外光谱的预处理、奇异样本筛选、多元校正和模型转移等技术及其在相关领域的应用.对近红外光谱大数据分析技术的初步研究,包括近红外光谱在工业品在线检测、不同批次产品鉴别中的应用以及近红外光谱物联网系统等也进行了综述.此外,对于近红外光谱大数据未来的发展及近红外光谱大数据云平台的基本功能、软硬件的设计与开发、建设过程中需要解决的问题等进行了详细阐述. | 刘言 蔡文生 邵学广 | 2015 | 科学通报2015，60，8： | 14 |
| 2 | 大数据与化学数据挖掘显示文摘数据是重要的战略资源,大数据挖掘技术已成为学术界、企业界甚至各国政府关注的热点.本文介绍了大数据的基本概念及发展现状,综述了与化学研究有关的大数据研究状况,讨论了大数据在基础理论与关键技术2个层面上的主要问题以及大数据挖掘技术在化学各领域中的应用,并对大数据发展的未来及其在化学学科中的应用前景进行了展望. | 刘言 蔡文生 邵学广 | 2015 | 科学通报2015，60，8： | 14 |
| 3 | Rapid recognition of Chinese herbal pieces of Areca catechu by different concocted processes using Fourier transform mid-infrared and near-infrared spectroscopy combined with partial least-squares discriminant analysis显示文摘Rapid and sensitive recognition of herbal pieces according to different concocted processing is crucial to quality control and pharmaceutical effect.Near-infrared(NIR) and mid-infrared(MIR) technology combined with supervised pattern recognition based on partial least-squares discriminant analysis (PLSDA) was attempted to classify and recognize six different concocted processing pieces of 600 Areca catechu L.samples and the influence of fingerprint information preprocessing methods on recognition performance was also investigated in this work.Recognition rates of 99.24%,100%and 99.49%for original fingerprint,multiple scatter correct(MSC) fingerprint and second derivative(2nd derivative) fingerprint of NIR spectra were achieved by PLSDA models,respectively.Meanwhile,a perfect recognition rate of 100%was obtained for the above three fingerprint models of MIR spectra.In conclusion.PLSDA can rapidly and effectively extract otherness of fingerprint information from NIR and MIR spectra to identify different concocted herbal pieces of A.catechu. | Hai-Yan Fu Dong-Chen Huang Tian-Ming Yang Yuan-Bin She Hao Zhang | 2013 | Chinese Chemical Letters2013，24，7： | 11 |
| 4 | Pretreating near infrared spectra with fractional order Savitzky–Golay differentiation(FOSGD)显示文摘With the aid of Riemann–Liouville fractional calculus theory,fractional order Savitzky–Golay differentiation(FOSGD) is calculated and applied to pretreat near infrared(NIR) spectra in order to improve the performance of multivariate calibrations.Similar to integral order Savitzky–Golay differentiation(IOSGD),FOSGD is obtained by fitting a spectral curve in a moving window with a polynomial function to estimate its coefficients and then carrying out the weighted average of the spectral curve in the window with the coefficients.Three NIR datasets including diesel,wheat and corn datasets were utilized to test this method.The results showed that FOSGD,which is easy to compute,is a general method to obtain Savitzky–Golay smoothing,fractional order and integral order differentiations.Fractional order differentiation computation to the NIR spectra often improves the performance of the PLS model with smaller RMSECV and RMSEP than integral order ones,especially for physical properties of interest,such as density,cetane number and hardness. | Kai-Yi Zheng Xuan Zhang Pei-Jin Tong Yuan Yao Yi-Ping Du | 2015 | Chinese Chemical Letters2015，26，3： | 3 |
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