Search Results - "Chemometrics and intelligent laboratory systems"

Review on data-driven modeling and monitoring for plant-wide industrial processes by Ge, Zhiqiang

“…Data-driven modeling and applications in plant-wide processes have recently caught much attention in both academy and industry. This paper provides a…”
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Particle swarm optimization (PSO). A tutorial by Marini, Federico, Walczak, Beata

“…Swarm-based algorithms emerged as a powerful family of optimization techniques, inspired by the collective behavior of social animals. In particle swarm…”
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mdatools – R package for chemometrics by Kucheryavskiy, Sergey

“…The paper describes mdatools – R package, which implements mainly basic but also some advanced chemometric methods providing a unified interface and user…”
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Be aware of error measures. Further studies on validation of predictive QSAR models by Roy, Kunal, Das, Rudra Narayan, Ambure, Pravin, Aher, Rahul B.

“…Validation is the most crucial concept for development and application of quantitative structure–activity relationship (QSAR) models. The validation process…”
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LightGBM-PPI: Predicting protein-protein interactions through LightGBM with multi-information fusion by Chen, Cheng, Zhang, Qingmei, Ma, Qin, Yu, Bin

“…Protein-protein interactions (PPIs) play an important role in cell life activities such as transcriptional regulation, signal transduction and drug signal…”
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Modern practical convolutional neural networks for multivariate regression: Applications to NIR calibration by Cui, Chenhao, Fearn, Tom

“…In this study, we investigate the use of convolutional neural networks (CNN) for near infrared (NIR) calibration. We propose a unified CNN structure that can…”
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On a simple approach for determining applicability domain of QSAR models by Roy, Kunal, Kar, Supratik, Ambure, Pravin

“…Quantitative structure–activity/property/toxicity relationship (QSAR/QSPR/QSTR) modeling has been used in medicinal chemistry, material sciences, environmental…”
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zCompositions — R package for multivariate imputation of left-censored data under a compositional approach by Palarea-Albaladejo, Javier, Martín-Fernández, Josep Antoni

“…zCompositions is an R package for the imputation of left-censored data under a compositional approach. It is pertinent when the analyst assumes that the…”
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Artificial intelligence-based single and hybrid models for prediction of water quality in rivers: A review by Rajaee, Taher, Khani, Salar, Ravansalar, Masoud

“…The need for accurate predictions of water quality in rivers has encouraged researchers to develop new methods and to improve the predictive ability of…”
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Multivariate comparison of classification performance measures by Ballabio, Davide, Grisoni, Francesca, Todeschini, Roberto

“…The assessment of the classification performance can be based on class indices, such as sensitivity, specificity and precision, which describe the…”
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libPLS: An integrated library for partial least squares regression and linear discriminant analysis by Li, Hong-Dong, Xu, Qing-Song, Liang, Yi-Zeng

“…Partial least squares (PLS) have gained wide applications especially in chemometrics, metabolomics/metabonomics as well as bioinformatics. Here, we present…”
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A review of variable selection methods in Partial Least Squares Regression by Mehmood, Tahir, Liland, Kristian Hovde, Snipen, Lars, Sæbø, Solve

“…With the increasing ease of measuring multiple variables per object the importance of variable selection for data reduction and for improved interpretability…”
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A tutorial on automatic hyperparameter tuning of deep spectral modelling for regression and classification tasks by Passos, Dário, Mishra, Puneet

“…Deep spectral modelling for regression and classification is gaining popularity in the chemometrics domain. A major topic in the deep learning (DL) modelling…”
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An automated Residual Exemplar Local Binary Pattern and iterative ReliefF based COVID-19 detection method using chest X-ray image by Tuncer, Turker, Dogan, Sengul, Ozyurt, Fatih

“…Coronavirus is normally transmitted from animal to person, but nowadays it is transmitted from person to person by changing its form. Covid-19 appeared as a…”
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A review on autoencoder based representation learning for fault detection and diagnosis in industrial processes by Qian, Jinchuan, Song, Zhihuan, Yao, Yuan, Zhu, Zheren, Zhang, Xinmin

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Ensemble deep kernel learning with application to quality prediction in industrial polymerization processes by Liu, Yi, Yang, Chao, Gao, Zengliang, Yao, Yuan

“…For predicting the melt index (MI) in industrial polymerization processes, traditional data-driven empirical models do not utilize the information in a large…”
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Data-driven monitoring of multimode continuous processes: A review by Quiñones-Grueiro, Marcos, Prieto-Moreno, Alberto, Verde, Cristina, Llanes-Santiago, Orestes

“…The Internet of Things benefits connectivity and functionality in industrial environments, while Cloud Computing boosts computational capability. Hence,…”
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A synergistic use of chemometrics and deep learning improved the predictive performance of near-infrared spectroscopy models for dry matter prediction in mango fruit by Mishra, Puneet, Passos, Dário

“…This study provides an innovative approach to improve deep learning (DL) models for spectral data processing with the use of chemometrics knowledge. The…”
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Review of soft sensor methods for regression applications by Souza, Francisco A.A., Araújo, Rui, Mendes, Jérôme

“…Soft sensors for regression applications (SSR) are inferential models that use online available sensors (e.g. temperature, pressure, flow rate, etc.) to…”
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Accurate prediction of nanofluid viscosity using a multilayer perceptron artificial neural network (MLP-ANN) by Heidari, Elham, Sobati, Mohammad Amin, Movahedirad, Salman

“…Viscosity is a significant physical property of nanofluids in practical heat transfer applications. No general model is capable for accurate prediction of…”
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