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Robust PCR and Robust PLSR: a Comparative Study
2004Principal Component Regression (PCR) and Partial Least Squares Regression (PLSR) are the two most popular regression techniques in chemo-metrics. They both fit a linear relationship between two sets of variables. The responses are usually low-dimensional whereas the regressors are very numerous compared to the number of observations.
Engelen, S. +3 more
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A hyperspectral GA-PLSR model for prediction of pine wilt disease
Multimedia Tools and Applications, 2019Pine wilt disease caused by a forest-invasive alien species, the pine wood nematode (Bursaphelenchus xylophilus) is considered as one of the most destructive pest problems. In recent years, spectroscopic technologies have shown great potentials for the assessment of forest damage due to their nondestructive, noninvasive, cost-effective, and rapidly ...
Sulan Zhang +3 more
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Modeling greenhouse temperature by means of PLSR and BPNN
2016 35th Chinese Control Conference (CCC), 2016To achieve the precise control of the greenhouse, further enhance energy efficiency, it is necessary to clearly understand the greenhouse temperature system's characteristics. This work is concerned with the greenhouse temperature system in the typical summer climate under east-central China conditions.
Xiao Feng Li +3 more
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ISA Transactions, 2015
In this paper, a robust hybrid model integrating an enhanced inputs based extreme learning machine with the partial least square regression (PLSR-EIELM) was proposed. The proposed PLSR-EIELM model can overcome two main flaws in the extreme learning machine (ELM), i.e. the intractable problem in determining the optimal number of the hidden layer neurons
Yan-Lin, He +3 more
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In this paper, a robust hybrid model integrating an enhanced inputs based extreme learning machine with the partial least square regression (PLSR-EIELM) was proposed. The proposed PLSR-EIELM model can overcome two main flaws in the extreme learning machine (ELM), i.e. the intractable problem in determining the optimal number of the hidden layer neurons
Yan-Lin, He +3 more
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Motion Reconstruction from Sparse Accelerometer Data Using PLSR
2012 Ninth International Conference on Wearable and Implantable Body Sensor Networks, 2012Detailed motion reconstruction is a prerequisite of biomotion analysis and physical function assessment for a variety of scenarios. For example, biomechanical analysis can be used to assess physical activity to diagnose pathological conditions, to provide an objective measure of biomechanics for peri-operative care, and to monitor patients with ...
Charence Wong +4 more
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Quantitative determination of Auramine O by terahertz spectroscopy with 2DCOS-PLSR model
Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2017Residues of harmful dyes such as Auramine O (AO) in herb and food products threaten the health of people. So, fast and sensitive detection techniques of the residues are needed. As a powerful tool for substance detection, terahertz (THz) spectroscopy was used for the quantitative determination of AO by combining with an improved partial least-squares ...
Huo, Zhang +3 more
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Selection of individual variables versus intervals of variables in PLSR
Journal of Chemometrics, 2010AbstractThe selection abilities of the two well‐known techniques of variable selection, synergy interval‐partial least‐squares (SiPLS) and genetic algorithm‐partial least‐squares (GA‐PLS), have been examined and compared. By using different simulated and real (corn and metabolite) datasets, keeping in view the spectral overlapping of the components ...
Masoud Shariati‐Rad, Masoumeh Hasani
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Relationship Between Size of Injected Microspheres and Ultrasound Imaging of Heart by PLSR
Pharmaceutical Research, 1997To investigate the enhancement in ultrasound signal (US) in heart, for diagnostic purposes, as a function of size and number of injected air-filled microspheres by multivariate statistical methods.The US enhancement in left ventricle was measured after injection of 31 suspensions of air-filled albumin microspheres divided on and injected in six dogs ...
K, Dyrstad, P C, Sontum
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Quantitative Steganalysis Based on Wavelet Domain HMT and PLSR
2011 10th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, 2011Aiming at the problem of estimation of secret message length in steganalysis, this paper presents a quantitative steganalysis method based on HMT (Hidden Markov Tree) and PLSR (Partial Least Squares Regression) to solve the problem. In this paper, three 2-State HMT models are modeled respectively for wavelet coefficients in the horizontal, vertical and
Ziwen Sun, Hui Li
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Application of PLSR with a comparison of MATLAB classification learner app in using BCI
2017 25th Signal Processing and Communications Applications Conference (SIU), 2017By using a brain-computer interface system (BCIs) humans can be enable direct communication with a computer or electronic device. In our previous works, we proved that gaze on the different rotation vanes causes a different effects on EEG signals. This paper proffers a novel BCI system based on this issue.
Masoud Maleki +2 more
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