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Intelligent Soft Sensors

This Special Issue deals with the field of intelligent soft sensors that enable the online estimation of nonmeasurable process variables. Soft sensors or virtual sensors are common names for software algorithms in which multiple measurements are processed together. Typically, soft sensors are based...

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Bibliographic Details
Main Author: Tomažič, Simon
Format: eBook
Language:English
Published: MDPI - Multidisciplinary Digital Publishing Institute 2023
Subjects:
Residual Model
Multi-source Data Fusion
Extreme Learning Machine
Bioprocess Monitoring
N/a
Total Intravenous Anesthesia
Nonlinear Systems
Nonlinear Regression Model
Observability
Modelling
History Of Engineering And Technology / Bicssc
Propofol
Pichia Pastoris
Image Feature Extraction
Variable Stiffness Actuation
Population-data-based Model
Technology: General Issues / Bicssc
Computerized Adaptive Testing (cat)
Joule Heating Effect
Early Fire Warning
State Estimation
Sintering Quality Prediction
Keyframe Extraction
Robust Observer
Depth Of Hypnosis
Neurodevelopmental Disorders
Simulator
Transfer Learning
Improved Mathematical Model
Soft-sensor Based Diagnosis
Non-linear Models
Intelligent Building System
Outliers
Bis Index
Least Squares Support Vector Machine
Frequency Analysis
Eda
Self-sensing Actuation
Stress Detection
Shape Memory Coil
Extended Kalman Filter
Support Vector Machine Regression Model
Soft Sensor
Physiological Signals
Soft Sensors
Hybrid Feature Fusion
D-s Evidence Theory
Affective Computing
Electrical Resistance
Variable Selection
Sensor Selection
Prognostic And Health Management
Kinetic Model
Spectroscopy
General Anesthesia
Target-controlled Infusion
Executive Functions
Raman
Improved Particle Swarm Algorithm
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary:This Special Issue deals with the field of intelligent soft sensors that enable the online estimation of nonmeasurable process variables. Soft sensors or virtual sensors are common names for software algorithms in which multiple measurements are processed together. Typically, soft sensors are based on control theory and are also referred to as state observers. There may be dozens or even hundreds of measurements from hard sensors (big data). The interaction of signals can be used to compute new quantities that cannot be measured directly online or are difficult and expensive to measure. Soft sensors are particularly useful in data fusion, combining measurements of different characteristics and dynamics. They can be used for fault diagnosis (self-analysis, self-calibration, and self-maintenance) as well as for control applications. Well-known software algorithms that can be seen as soft sensors include, for example, Kalman filters. More recent implementations of soft sensors use neural networks, fuzzy logic, models based on evolving clustering, partial least squares, etc. In the digitized factories of the future, intelligent sensors represent one of the core building blocks for automating and optimizing production, as they make production more efficient in every respect.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
Physical Description:1 electronic resource (230 p.)
ISBN:books978-3-0365-8523-9
9783036585239
9783036585222

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