The current use of a single chemical component as the representative quality control marker of herbal food supplement is inadequate. In this CD80-Quantitative-Pattern-Activity-Relationship (QPAR) study, we built a bioactivity predictive model that can be applicable for complex mixtures. Through integrating the chemical fingerprinting profiles of the immunomodulating herb Radix Astragali (RA) ex...

Abstract: This paper develops an offset free tracking model predictive control based on a dynamic partial least square (PLS) framework. First, state space model is used as the inner model of PLS to describe the dynamic system, where subspace identification method is used to identify the inner model. Based on the obtained model, multiple independent model predictive control (MPC) controllers are...

In this article, we consider prediction of a univariate response from background data. The data may have a near-collinear structure and additionally group effects are assumed to exist. A two step estimation procedure is proposed. The first step is to summarize the information in the predictors via a bilinear model. The bilinear model has a Krylov structured within individual design matrix, whic...

This paper proposes a hybrid scheme to set the weights initialization and the optimal number of hidden nodes of the backpropagation network (BPN) by applying the loading weights and factor numbers of the partial least-squares (PLS) algorithm. The joint PLS and BPN method (PLSBPN) starts with a small residual error, modi6es the latent weight matrices, and obtains a near-global minimum in the cal...

This paper presents regression models obtained from a process of blind prediction of peptide binding affinity from provided descriptors for several distinct datasets as part of the 2006 Comparative Evaluation of Prediction Algorithms (COEPRA) contest. This paper finds that kernel partial least squares, a nonlinear partial least squares (PLS) algorithm, outperforms PLS, and that the incorporatio...

forecasting of municipal waste generation is a critical challenge for decision making and planning,because proper planning and operation of a solid waste management system is intensively affected by municipal solid waste (msw) streams analysis and accurate predictions of solid waste quantities generated. due to dynamic and complexity of solid waste management system, models by artificial intell...

4 Hands-on 3 4.1 Loading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 4.2 Principal Component Analysis (PCA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 4.3 Partial least-squares: PLS and PLS-DA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 4.4 Orthogonal partial least square...

Partial Least Squares (PLS) is a statistical technique that is widely used in the Partial Least Squares (PLS) is a popular technique for estimating structural equation models with latent variables. It is frequently perceived as an alternative to covariance analysis of such models. While its proponents recognize the shortcomings of PLS for testing explanatory models in comparison to covariance m...