Projection to latent structures (PLS)model has beenwidely used in quality-related processmonitoring, as it can establish amapping relationship between process variables and quality index variables. To enhance the adaptivity of PLS, kernel PLS (KPLS) as an advanced version has been proposed for nonlinear processes. In this paper, we discuss a new total kernel PLS (T-KPLS) for nonlinear quality-r...

Genetic algorithm and partial least square (GA-PLS) and kernel PLS (GA-KPLS) techniques were used to investigate the correlation between retention indices (RI) and descriptors for 117 diverse compounds in essential oils from 5 Pimpinella species gathered from central Turkey which were obtained by gas chromatography and gas chromatography-mass spectrometry. The square correlation coefficient lea...

Simultaneous spectrophotometric determination of Mn, Zn and Co was studied by two methods, classical partial least-squares (PLS) and kernel partial least-squares (KPLS), with 2-(5-bromo-2- pyridylazo)-5-diethylaminephenol (5-Br-PADAP) and cetyl pyridinium bromide (CPB). Two programs, SPGRPLS and SPGRKPLS, were designed to perform the calculations. Eight error functions were calculated for deduc...

Shape is an important morphological characteristic both in animals and plants. In the present study, we examined a method for predicting biological contour shapes based on genome-wide marker polymorphisms. The method is expected to contribute to the acceleration of genetic improvement of biological shape via genomic selection. Grain shape variation observed in rice (Oryza sativa L.) germplasms ...

A novel KPLS-PLS batch monitoring and quality prediction approach based on fuzzy clustering soft-partition is proposed to solve the stage-transition monitoring and prediction problem in multistage batch processes. The proposed method calculates firstly similarity indices between different time-slice data matrices of batch processes, then phase division algorithm is designed by fuzzy clustering ...

The Degrees of Freedom of Kernel Partial Least Squares (KPLS) require all eigenvalues of the kernel matrix K, hence the computation is cubic in the number of observations n. •We use Kernel PLS itself to approximate the eigenvalues of the kernel matrix. −→ We can compute approximate Degrees of Freedom of KPS in O ( n2 ) ! •We can also compute approximate confidence intervals for KPLS in O ( n2 ) !

The terahertz (THz) spectra of rapeseed leaves with different water content (WC) were investigated. The transmission and absorption spectra in the range of 0.3-2 THz were measured by using THz time-domain spectroscopy. The mean transmittance and absorption coefficients were applied to analyze the change regulation of WC. In addition, the Savitzky-Golay method was performed to preprocess the spe...

In this paper, we propose a gene extraction method by using two standard feature extraction methods, namely the T-test method and kernel partial least squares (KPLS), in tandem. First, a preprocessing step based on the T-test method is used to filter irrelevant and noisy genes. KPLS is then used to extract features with high information content. Finally, the extracted features are fed into a cl...

I-vectors are concise representations of speaker characteristics. Recent progress in i-vectors related research has utilized their ability to capture speaker and channel variability to develop efficient automatic speaker verification (ASV) systems. Inter-speaker relationships in the i-vector space are nonlinear. Accomplishing effective speaker verification requires a good modeling of these non-...

Soft sensors are inferential estimators when the employment of hardware is inapplicable, expensive, or difficult in industrial plant processes. Currently, a simple soft sensor, namely locally weighted partial least squares (LW-PLS), which can cope with nonlinearity process, has been developed. However, LW-PLS exhibits disadvantages handling strong nonlinear process data. To address this problem...