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Near-Infrared Spectroscopy Combined with Absorbance Upper Optimization Partial Least Squares Applied to Rapid Analysis of Polysaccharide for Proprietary Chinese Medicine Oral Solution 被引量:2
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作者 Jiexiong Su Xinkai Gao +5 位作者 Lirong Tan Xianzhao Liu Yueqing Ye Yifang Chen Kaisheng Ma Tao Pan 《American Journal of Analytical Chemistry》 2016年第3期275-281,共7页
Near-infrared (NIR) spectroscopy was applied to reagent-free quantitative analysis of polysaccharide of a brand product of proprietary Chinese medicine (PCM) oral solution samples. A novel method, called absorbance up... Near-infrared (NIR) spectroscopy was applied to reagent-free quantitative analysis of polysaccharide of a brand product of proprietary Chinese medicine (PCM) oral solution samples. A novel method, called absorbance upper optimization partial least squares (AUO-PLS), was proposed and successfully applied to the wavelength selection. Based on varied partitioning of the calibration and prediction sample sets, the parameter optimization was performed to achieve stability. On the basis of the AUO-PLS method, the selected upper bound of appropriate absorbance was 1.53 and the corresponding wavebands combination was 400 - 1880 & 2088 - 2346 nm. With the use of random validation samples excluded from the modeling process, the root-mean-square error and correlation coefficient of prediction for polysaccharide were 27.09 mg·L<sup>-</sup><sup>1</sup> and 0.888, respectively. The results indicate that the NIR prediction values are close to those of the measured values. NIR spectroscopy combined with AUO-PLS method provided a promising tool for quantification of the polysaccharide for PCM oral solution and this technique is rapid and simple when compared with conventional methods. 展开更多
关键词 Near-Infrared Spectroscopic Analysis Proprietary Chinese Medicine Oral Solution POLYSACCHARIDE Absorbance Upper optimization Partial least squares
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Machine Learning for Smart Soil Monitoring
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作者 Khaoula Ben Abdellafou Kamel Zidi +2 位作者 Ahamed Aljuhani Okba Taouali Mohamed Faouzi Harkat 《Computers, Materials & Continua》 2025年第5期3007-3023,共17页
Environmental protection requires identifying,investigating,and raising awareness about safeguarding nature from the harmful effects of both anthropogenic and natural events.This process of environmental protection is... Environmental protection requires identifying,investigating,and raising awareness about safeguarding nature from the harmful effects of both anthropogenic and natural events.This process of environmental protection is essential for maintaining human well-being.In this context,it is critical to monitor and safeguard the personal environment,which includes maintaining a healthy diet and ensuring plant safety.Living in a balanced environment and ensuring the safety of plants for green spaces and a healthy diet require controlling the nature and quality of the soil in our environment.To ensure soil quality,it is imperative to monitor and assess the levels of various soil parameters.Therefore,an Optimized Reduced Kernel Partial Least Squares(ORKPLS)method is proposed to monitor and control soil parameters.This approach is designed to detect increases or deviations in soil parameter quantities.A Tabu search approach was used to select the appropriate kernel parameter.Subsequently,soil analyses were conducted to evaluate the performance of the developed techniques.The simulation results were analyzed and compared.Through this study,deficiencies or exceedances in soil parameter quantities can be identified.The proposed method involves determining whether each soil parameter falls within a normal range.This allows for the assessment of soil parameter conditions based on the principle of fault detection. 展开更多
关键词 Systems security soil analyses kernel partial least squares(KPLS) optimized reduced kernel partial least squares(ORKPLS) tabu search process monitoring machine learning fault detection(FD)
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Generalized Yule-walker and two-stage identification algorithms for dual-rate systems 被引量:2
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作者 Feng DING 《控制理论与应用(英文版)》 EI 2006年第4期338-342,共5页
In this paper, two approaches are developed for directly identifying single-rate models of dual-rate stochastic systems in which the input updating frequency is an integer multiple of the output sampling frequency. Th... In this paper, two approaches are developed for directly identifying single-rate models of dual-rate stochastic systems in which the input updating frequency is an integer multiple of the output sampling frequency. The first is the generalized Yule-Walker algorithm and the second is a two-stage algorithm based on the correlation technique. The basic idea is to directly identify the parameters of underlying single-rate models instead of the lifted models of dual-rate systems from the dual-rate input-output data, assuming that the measurement data are stationary and ergodic. An example is given. 展开更多
关键词 IDENTIFICATION ESTIMATION least squares optimization Multirate systems Dual-rate systems Correlation analysis Yule-walker algorithm.
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An Axisymmetric Numerical Model for Simulating Kinetically-Limited Growth of a Cylindrical Rod in 3D Laser-induced Chemical Vapor Deposition 被引量:1
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作者 R.Nassa, W.Z.Dai and Q.ChenMathematics & Statistics, College of Engineering & Science, Louisiana Tech. University, Ruston, LA 71272, USA 《Journal of Materials Science & Technology》 SCIE EI CAS CSCD 2002年第2期127-132,共6页
Laser-induced chemical vapor deposition (LCVD) is an important process for freeform microfabrication of high aspect ratio prototypes. The system consists of a laser beam focused onto a movable substrate in a vacuum ch... Laser-induced chemical vapor deposition (LCVD) is an important process for freeform microfabrication of high aspect ratio prototypes. The system consists of a laser beam focused onto a movable substrate in a vacuum chamber. Heat from the laser at or near the focal spot of the beam causes gas in the chamber to react. As a result, solid-phase reaction products are deposited on the substrate to form the microstructure. In this paper, we develop a numerical model for simulating growth of an axisymmetric cylindrical rod by pre-specifying the surface temperatures required for growing the rod and then by solving for the laser power that satisfies the pre-specified temperatures. The solution using least squares is obtained by minimizing the sum of square deviations between the pre-specified surface temperatures and the calculated temperatures from the heat equation with a given laser power as a heat source. Model predictions of the laser power over growth time helped in optimizing the growth process. Rods grown based on the predicted laser power from the numerical model were very close to being cylindrical in shape. Ways to further improve the model are being investigated. 展开更多
关键词 Numerical model LCVD Cylindrical rod growth least squares optimization
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AO-MW-PLS method applied to rapid quantification of teicoplanin with near-infrared spectroscopy 被引量:1
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作者 Jiemei Chen Tian Ai +2 位作者 Tao Pan Lijun Yao Fenggeng Xia 《Journal of Innovative Optical Health Sciences》 SCIE EI CAS 2017年第1期21-33,共13页
Teicoplanin(TCP)is an important lipoglycopeptide antibiotic produced by fermenting Acti-noplanes teichomyceticus.The change in TCP concentration is important to measure in the fermentation process.In this study,a reag... Teicoplanin(TCP)is an important lipoglycopeptide antibiotic produced by fermenting Acti-noplanes teichomyceticus.The change in TCP concentration is important to measure in the fermentation process.In this study,a reagent-free and rapid quantification method for TCP in the TCP-Tris-HCl mixture samples was developed using near infrared(NIR)spectroscopy by focusing our attention on the fermentation process for TCP.The absorbance optimization(AO)partial least squares(PLS)was proposed and integrated with the moving window(MW)PLS,which is called AO-MW-PLS method,to select appropriate wavebands.Amodel set that includes various wavebands that were equivalent to the optimal AO-MW-PLS waveband was,proposed based on statistical considerations.The public region of all equivalent wavebands was just one of the equivalent wavebands.The obtained public regions were 1540-1868 nm for TCP and 1114-1310 nm for Tris.The root-mean-square error and correlation coeficient for leave-one-out cross validation were 0.046 mg mL^(-1)and 0.9998 mg mL^(-1)for TCP,and 0.235 mg mL^(-1)and 0.9986 mg mL^(-1)for Tris,respectively.All the models achieved highly accurate prediction effects,and the selected wavebands provided valuable references for designing specialized spectrometers.This study provided a valuable reference for further application of the proposed methods to TCP fermentation broth and to other spectroscopic analysis fields. 展开更多
关键词 TEICOPLANIN near-infrared spectroscopic analysis absorbance optimization partial least squares moving window partial least squares equivalent model set
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Human motion prediction using optimized sliding window polynomial fitting and recursive least squares 被引量:3
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作者 Li Qinghua Zhang Zhao +3 位作者 Feng Chao Mu Yaqi You Yue Li Yanqiang 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2021年第3期76-85,110,共11页
Human motion prediction is a critical issue in human-robot collaboration(HRC)tasks.In order to reduce the local error caused by the limitation of the capture range and sampling frequency of the depth sensor,a hybrid h... Human motion prediction is a critical issue in human-robot collaboration(HRC)tasks.In order to reduce the local error caused by the limitation of the capture range and sampling frequency of the depth sensor,a hybrid human motion prediction algorithm,optimized sliding window polynomial fitting and recursive least squares(OSWPF-RLS)was proposed.The OSWPF-RLS algorithm uses the human body joint data obtained under the HRC task as input,and uses recursive least squares(RLS)to predict the human movement trajectories within the time window.Then,the optimized sliding window polynomial fitting(OSWPF)is used to calculate the multi-step prediction value,and the increment of multi-step prediction value was appropriately constrained.Experimental results show that compared with the existing benchmark algorithms,the OSWPF-RLS algorithm improved the multi-step prediction accuracy of human motion and enhanced the ability to respond to different human movements. 展开更多
关键词 human-robot collaboration(HRC) human motion prediction sliding window polynomial fitting(SWPF)algorithm recursive least squares(RLS) optimized sliding window polynomial fitting and recursive least squares(OSWPF-RLS)
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NEW RESULTS ABOUT THE RELATIONSHIP BETWEEN OPTIMALLY WEIGHTED LEAST SQUARES ESTIMATE AND LINEAR MINIMUM VARIANCE ESTIMATE
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作者 Juan ZHAO Yunmin ZHU 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2009年第1期137-149,共13页
The optimally weighted least squares estimate and the linear minimum variance estimateare two of the most popular estimation methods for a linear model.In this paper,the authors makea comprehensive discussion about th... The optimally weighted least squares estimate and the linear minimum variance estimateare two of the most popular estimation methods for a linear model.In this paper,the authors makea comprehensive discussion about the relationship between the two estimates.Firstly,the authorsconsider the classical linear model in which the coefficient matrix of the linear model is deterministic,and the necessary and sufficient condition for equivalence of the two estimates is derived.Moreover,under certain conditions on variance matrix invertibility,the two estimates can be identical providedthat they use the same a priori information of the parameter being estimated.Secondly,the authorsconsider the linear model with random coefficient matrix which is called the extended linear model;under certain conditions on variance matrix invertibility,it is proved that the former outperforms thelatter when using the same a priori information of the parameter. 展开更多
关键词 Conditional expectation linear minimum variance estimation necessary and sufficient condition optimally weighted least squares estimation.
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Model parameters estimation of aero-engine based on hybrid optimization algorithm 被引量:1
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作者 LI Qiu-hong LI Ye-bo JIANG Dian-wen 《航空动力学报》 EI CAS CSCD 北大核心 2011年第7期1665-1671,共7页
A hybrid optimization algorithm for the time-domain identification of multivariable,state space model for aero-engine was presented in this paper.The optimization procedure runs particle swarm optimization(PSO) and le... A hybrid optimization algorithm for the time-domain identification of multivariable,state space model for aero-engine was presented in this paper.The optimization procedure runs particle swarm optimization(PSO) and least squares optimization(LSO) "in series".PSO starts from an initial population and searches for the optimum solution by updating generations.However,it can sometimes run into a suboptimal solution.Then LSO can start from the suboptimal solution of PSO,and get an optimum solution by conjugate gradient algorithm.The algorithm is suitable for the high-order multivariable system which has many parameters to be estimated in wide ranges.Hybrid optimization algorithm is applied to estimate the parameters of a 4-input 4-output state variable model(SVM) for aero-engine.The simulation results demonstrate the effectiveness of the proposed algorithm. 展开更多
关键词 AERO-ENGINE state variable model(SVM) particle swarm optimization(PSO) least squares optimization(LSO) hybrid optimization algorithm
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