Single‐object localization using multiple ultrasonic sensors and constrained weighted least‐squares method
Sign Up to like & getrecommendations! Published in 2021 at "Asian Journal of Control"
DOI: 10.1002/asjc.2491
Abstract: In this paper, an active single‐object localization system with U‐shaped ultrasonic module array is presented. The proposed algorithm in this system has two stages. The first stage is time‐of‐flight (TOF) estimation of reflected ultrasonic signals.… read more here.
Keywords: single object; squares method; localization; least squares ... See more keywords
Determinants of Generative AI in Promoting Green Purchasing Behavior: A Hybrid Partial Least Squares–Artificial Neural Network Approach
Sign Up to like & getrecommendations! Published in 2025 at "Business Strategy and the Environment"
DOI: 10.1002/bse.4186
Abstract: In the era of rapid technological advancement, generative artificial intelligence (AI) has emerged as a transformative force in various sectors, including environmental sustainability. This research investigates the factors and consequences of using generative AI to… read more here.
Keywords: least squares; determinants generative; green purchasing; artificial neural ... See more keywords
Robust iteratively reweighted SIMPLS
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Chemometrics"
DOI: 10.1002/cem.2881
Abstract: Partial least squares regression is a very powerful multivariate regression technique to model multicollinear data or situation where the number of explanatory variables is larger than the sample size. Two algorithms, namely, Non‐linear Iterative Partial… read more here.
Keywords: reweighted simpls; least squares; iteratively reweighted; robust iteratively ... See more keywords
A frequency‐localized recursive partial least squares ensemble for soft sensing
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DOI: 10.1002/cem.2999
Abstract: We report the use of a frequency‐localized adaptive soft sensor ensemble using the wavelet coefficients of the responses from the physical sensors. The proposed method is based on building recursive, partial least squares soft sensor… read more here.
Keywords: soft sensor; least squares; recursive partial; wavelet ... See more keywords
Local partial least squares based on global PLS scores
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Chemometrics"
DOI: 10.1002/cem.3117
Abstract: A local‐based method for near‐infrared spectroscopy predictions, the local partial least squares regression on global PLS scores (LPLS‐S), is proposed in this work and compared with the usual local PLS (LPLS) regression approach. LPLS‐S is… read more here.
Keywords: pls; least squares; local partial; lpls ... See more keywords
Application of infrared microscopy and alternating least squares to the forensic analysis of automotive paint chips
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Chemometrics"
DOI: 10.1002/cem.3277
Abstract: To collect infrared (IR) absorbance spectra from an automotive paint chip with an IR imaging microscope, it is a common practice to cast the paint chip in epoxy and then cross section it using a… read more here.
Keywords: paint; least squares; microscopy; automotive paint ... See more keywords
Adaptive soft sensor modeling of chemical processes based on an improved just‐in‐time learning and random mapping partial least squares
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Chemometrics"
DOI: 10.1002/cem.3554
Abstract: The just‐in‐time learning‐based partial least squares (JIT‐PLS) has been extensively applied to adaptive soft sensor modeling of complex nonlinear processes. However, it still has the problems of unreasonable relevant samples selection and unsatisfactory local modeling.… read more here.
Keywords: time learning; least squares; random mapping; partial least ... See more keywords
Evaluation of Classical Least Squares Discriminant Analysis (CLS‐DA) as a Novel Supervised Pattern Recognition Technique
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Chemometrics"
DOI: 10.1002/cem.3609
Abstract: Multivariate calibration techniques and machine learning algorithms are inextricably linked within the realm of chemometrics and data analysis. Classical least squares (CLS) modeling, a fundamental multivariate regression approach, has traditionally been utilized for quantitative analysis… read more here.
Keywords: classical least; least squares; pattern recognition; analysis ... See more keywords
Using Quantile and Asymmetric Least Squares Regression for Optimal Risk Adjustment
Sign Up to like & getrecommendations! Published in 2017 at "Health Economics"
DOI: 10.1002/hec.3352
Abstract: In this paper, we analyze optimal risk adjustment for direct risk selection (DRS). Integrating insurers' activities for risk selection into a discrete choice model of individuals' health insurance choice shows that DRS has the structure… read more here.
Keywords: risk adjustment; optimal risk; least squares; squares regression ... See more keywords
Optimized reconstruction of the absorption spectra of kidney tissues from the spectra of tissue components using the least squares method.
Sign Up to like & getrecommendations! Published in 2024 at "Journal of biophotonics"
DOI: 10.1002/jbio.202300466
Abstract: With the objective of developing new methods to acquire diagnostic information, the reconstruction of the broadband absorption coefficient spectra (μa[λ]) of healthy and chromophobe renal cell carcinoma kidney tissues was performed. By performing a weighted… read more here.
Keywords: least squares; absorption spectra; kidney tissues; using least ... See more keywords
Linear calibrations in chromatography: the incorrect use of ordinary least squares for determinations at low levels, and the need to redefine the limit of quantification with this regression model.
Sign Up to like & getrecommendations! Published in 2020 at "Journal of separation science"
DOI: 10.1002/jssc.202000094
Abstract: Ordinary least squares is widely applied as the standard regression method for analytical calibrations, and it is usually accepted that this regression method can be used for quantification starting at the limit of quantification. However,… read more here.
Keywords: limit quantification; ordinary least; least squares; low levels ... See more keywords