Results 251 to 260 of about 3,351,616 (311)
Some of the next articles are maybe not open access.
Soft Sensor Network for Environmental Monitoring
2016This paper shows the application of a soft sensor network for the detection of meteorological events. A set of hard (real) sensor are placed in a territory, where they measure heterogeneous quantities. Starting from their measurements, a soft sensor network provides useful information coming from the data.
Maniscalco U, Pilato G, Vella F
openaire +2 more sources
Supervised Variational Autoencoders for Soft Sensor Modeling With Missing Data
IEEE Transactions on Industrial Informatics, 2020Autoencoder (AE) is a deep neural network that has been widely utilized in process industry owing to its superior abilities of feature extraction and data reconstruction.
Ruimin Xie +4 more
semanticscholar +1 more source
IEEE Transactions on Cybernetics, 2020
These days, data-driven soft sensors have been widely applied to estimate the difficult-to-measure quality variables in the industrial process. How to extract effective feature representations from complex process data is still the difficult and hot spot
Qingqiang Sun, Zhiqiang Ge
semanticscholar +1 more source
These days, data-driven soft sensors have been widely applied to estimate the difficult-to-measure quality variables in the industrial process. How to extract effective feature representations from complex process data is still the difficult and hot spot
Qingqiang Sun, Zhiqiang Ge
semanticscholar +1 more source
, 2020
Hierarchical local nonlinear dynamic feature learning is of great importance for soft sensor modeling in process industry. Convolutional neural network (CNN) is an excellent local feature extractor that is suitable for process data representation.
Xiaofeng Yuan +3 more
semanticscholar +1 more source
Hierarchical local nonlinear dynamic feature learning is of great importance for soft sensor modeling in process industry. Convolutional neural network (CNN) is an excellent local feature extractor that is suitable for process data representation.
Xiaofeng Yuan +3 more
semanticscholar +1 more source
Fully 3D‐Printed Soft Capacitive Sensor of High Toughness and Large Measurement Range
Advancement of scienceSoft capacitive sensors are widely utilized in wearable devices, flexible electronics, and soft robotics due to their high sensitivity. However, they may suffer delamination and/or debonding due to their low interfacial toughness.
Fei Xiao +5 more
semanticscholar +1 more source
IEEE Transactions on Neural Networks and Learning Systems, 2020
Soft sensor techniques have been applied to predict the hard-to-measure quality variables based on the easy-to-measure process variables in industry scenarios.
Liangjun Feng, Chunhui Zhao, Youxian Sun
semanticscholar +1 more source
Soft sensor techniques have been applied to predict the hard-to-measure quality variables based on the easy-to-measure process variables in industry scenarios.
Liangjun Feng, Chunhui Zhao, Youxian Sun
semanticscholar +1 more source
2021
The demand for interfacing electronics in everyday life is rapidly accelerating, with an ever-growing number of applications in wearable electronics and electronic skins for robotics, prosthetics, and other purposes. Soft sensors that efficiently detect environmental or biological/physiological stimuli have been extensively studied due to their ...
Roels, Ellen +6 more
openaire +1 more source
The demand for interfacing electronics in everyday life is rapidly accelerating, with an ever-growing number of applications in wearable electronics and electronic skins for robotics, prosthetics, and other purposes. Soft sensors that efficiently detect environmental or biological/physiological stimuli have been extensively studied due to their ...
Roels, Ellen +6 more
openaire +1 more source
Soft sensor model for dynamic processes based on multichannel convolutional neural network
, 2020Soft sensors have been extensively used to predict the difficult-to-measure key quality variables. The robust soft sensors should be able to sufficiently extract the local dynamic and nonlinear features of process data for accurate prediction ...
Xiaofeng Yuan +5 more
semanticscholar +1 more source
2008 7th World Congress on Intelligent Control and Automation, 2008
An improved least squares support vector machine (LS-SVM) approach was proposed to overcome the drawback of ldquolosing sparsityrdquo in original LS-SVM. At the same time, real-coded genetic algorithm (RC-GA) was introduced to solve the difficult problem of parameters selection in LS-SVM.
null Zhenrui Peng +2 more
openaire +1 more source
An improved least squares support vector machine (LS-SVM) approach was proposed to overcome the drawback of ldquolosing sparsityrdquo in original LS-SVM. At the same time, real-coded genetic algorithm (RC-GA) was introduced to solve the difficult problem of parameters selection in LS-SVM.
null Zhenrui Peng +2 more
openaire +1 more source
Soft Sensors Map Skin Mechanics
Chemical & Engineering News Archive, 2015An international research team led by John A. Rogers of the University of Illinois, Urbana-Champaign, has built electronic, flexible patches that can measure the mechanical properties of skin and other biological tissue (Nat. Mater. 2015, DOI: 10.1038/nmat4289). The researchers mapped the skin elasticity of dozens of patients in the clinic, building up
openaire +1 more source