Protein is an important component of milk powder. The fast and non-destructive detection of protein content in milk powder is important. Infrared spectroscopy technique was applied to achieve this purpose. Least-squares support vector machine (LS-SVM) was applied to building the protein prediction model based on spectral transmission rate. The determination coefficient for prediction (R2pÞ was ...

In view of the remarkable time–frequency property obtained fromwavelet packets and the excellent generalization ability derived from the least squares support vector machine (LS SVM), a novel approach is proposed, which focuses on the research on state detection for pressure vessels. The minimum entropy criterion is adopted to realize the optimal wavelet packet decomposition, the feature vector...

In least squares support vector (LS-SVM), the key challenge lies in the selection of free parameters such as kernel parameters and tradeoff parameter. However, when a large number of free parameters are involved in LS-SVM, the commonly used grid search method for model selection is intractable. In this paper, SLOO-MPS is proposed for tuning multiple parameters for LS-SVM to overcome this proble...

in the current study, both ligand-based molecular docking and receptor-based quantitative structure activity relationships (qsar) modeling were performed on 35 diaryl urea derivative inhibitors of v600e b-raf. in this qsar study, a linear (multiple linear regressions) and a nonlinear (partial least squares least squares support vector machine (pls-ls-svm)) were used and compared. the predictive...

A scheme of direct adaptive H∞ control based on least squares support vector machines (LS-SVM) is proposed for a class of nonlinear uncertain systems. In this method, LS-SVM is employed to construct the adaptive controller, and an on-line learning rule for the weighting vector and bias is derived. A parameter selection method based on the genetic algorithm (GA) is given for LS-SVM regression wi...

Least-Squares Support Vector Machines (LS-SVMs) have been successfully applied in many classification and regression tasks. Their main drawback is the lack of sparseness of the final models. Thus, a procedure to sparsify LS-SVMs is a frequent desideratum. In this paper, we adapt to the LS-SVM case a recent work for sparsifying classical SVM classifiers, which is based on an iterative approximat...

Most of the existing color image watermarking schemes were designed to mark the image luminance component only, which have some disadvantages: (i) they are sensitive to color attacks because of ignoring the correlation between different color channels, (ii) they are always not robust to geometric distortions for neglecting the watermark desynchronization. It is a challenging work to design a ro...

Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) technologies can overcome the drawbacks of the individual systems. One of the advantages is that the integrated solution can provide continuous navigation capability even during GPS outages. However, bridging the GPS outages is still a challenge when Micro-Electro-Mechanical System (MEMS) inertial sensors are us...