Results 61 to 70 of about 3,502,968 (324)
The Chaotic Prediction for Aero-Engine Performance Parameters Based on Nonlinear PLS Regression
Journal of Applied Mathematics, 2012 The prediction of the aero-engine performance parameters is very important for aero-engine condition monitoring and fault diagnosis. In this paper, the chaotic phase space of engine exhaust temperature (EGT) time series which come from actual air-borne ...
Chunxiao Zhang, Junjie Yue
doaj +1 more source
Advanced Science, EarlyView.Multidrug‐resistant Vibrio infections are rising rapidly and threaten coastal populations worldwide. This study introduces D‐zp37, a chirality‐engineered antimicrobial peptide with exceptional potency against resistant Vibrio species. D‐zp37 kills planktonic cells, blocks mixed‐species biofilms, disrupts essential bacterial stress responses, and shows ...
Ping Zeng +11 more
wiley +1 more source
Metabolites, 2016 Partial least squares (PLS) is one of the most commonly used supervised modelling approaches for analysing multivariate metabolomics data. PLS is typically employed as either a regression model (PLS-R) or a classification model (PLS-DA).
Yun Xu +4 more
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FTIR Spectrometry with PLS Regression for Rapid TBN Determination of Worn Mineral Engine Oils
Energies, 2020 The TBN (Total Base Number) parameter is generally recognized by both engine oil processors and engine manufacturers as a key factor of oil quality.
Marie Sejkorová +3 more
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Feature Extraction in Signal Regression: A Boosting Technique for Functional Data Regression [PDF]
, 2007 Main objectives of feature extraction in signal regression are the improvement of accuracy of prediction on future data and identification of relevant parts of the signal. A feature extraction procedure is proposed that uses boosting techniques to select
Gertheiss, Jan, Tutz, Gerhard
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Advanced Science, EarlyView.STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu +5 more
wiley +1 more source
Food Chemistry, 2018 The current study determined the applicability of sequential and orthogonalised-partial least squares (SO-PLS) regression to relate Cabernet Sauvignon grape chemical composition to the sensory perception of the corresponding wines. Grape samples (n = 25)
J. Niimi +5 more
semanticscholar +1 more source
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
Advanced Energy Materials, EarlyView.In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source
Revisiting useful approaches to data-rich macroeconomic forecasting [PDF]
, 2008 We compare a number of data-rich prediction methods that are widely used in macroeconomic forecasting with a lesser known alternative: partial least squares (PLS) regression.
Groen, Jan J. J., Kapetanios, George
core
Agribusiness, EarlyView.ABSTRACT Innovation is essential for competitiveness in agribusiness facing dynamic environments. This study examines how market orientation, marketing, relational, and social capabilities influence innovation performance. Using data from 751 Spanish firms and a multi‐method approach that integrates Structural Equation Modeling (PLS‐SEM), Necessary ...
Beatriz Corchuelo Martínez‐Azúa +1 more
wiley +1 more source