Related references
Note: Only part of the references are listed.Bidirectional stochastic configuration network for regression problems
Weipeng Cao et al.
NEURAL NETWORKS (2021)
Imputation of Missing Traffic Flow Data Using Denoising Autoencoders
Boyuan Jiang et al.
12TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT) / THE 4TH INTERNATIONAL CONFERENCE ON EMERGING DATA AND INDUSTRY 4.0 (EDI40) / AFFILIATED WORKSHOPS (2021)
Dynamic time warping-based imputation for univariate time series data
Thi-Thu-Hong Phan et al.
PATTERN RECOGNITION LETTERS (2020)
Supervised Variational Autoencoders for Soft Sensor Modeling With Missing Data
Ruimin Xie et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2020)
Traffic Flow Imputation Using Parallel Data and Generative Adversarial Networks
Yuanyuan Chen et al.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2020)
Missing Data Imputation for Geolocation-based Price Prediction Using KNN MCF Method
Karshiev Sanjar et al.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION (2020)
Imputing missing indoor air quality data via variational convolutional autoencoders: Implications for ventilation management of subway metro systems
Jorge Loy-Benitez et al.
BUILDING AND ENVIRONMENT (2020)
Improving Data Quality of Low-cost IoT Sensors in Environmental Monitoring Networks Using Data Fusion and Machine Learning Approach
Nwamaka U. Okafor et al.
ICT EXPRESS (2020)
Evaluation and calibration of a low-cost particle sensor in ambient conditions using machine-learning methods
Minxing Si et al.
ATMOSPHERIC MEASUREMENT TECHNIQUES (2020)
Analysing the performance of low-cost air quality sensors, their drivers, relative benefits and calibration in citiesa case study in Sheffield
Said Munir et al.
ENVIRONMENTAL MONITORING AND ASSESSMENT (2019)
Artificial Neural Networks with Random Weights for Incomplete Datasets
Diego P. P. Mesquita et al.
NEURAL PROCESSING LETTERS (2019)
In Situ Calibration Algorithms for Environmental Sensor Networks: A Review
Florentin Delaine et al.
IEEE SENSORS JOURNAL (2019)
Calibration of a low-cost PM2.5 monitor using a random forest model
Yanwen Wang et al.
ENVIRONMENT INTERNATIONAL (2019)
A Bayesian tensor decomposition approach for spatiotemporal traffic data imputation
Xinyu Chen et al.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2019)
Regression methods in the calibration of low-cost sensors for ambient particulate matter measurements
Marek Badura et al.
SN APPLIED SCIENCES (2019)
A review on neural networks with random weights
Weipeng Cao et al.
NEUROCOMPUTING (2018)
Using statistical methods to carry out in field calibrations of low cost air quality sensors
Jose Maria Cordero et al.
SENSORS AND ACTUATORS B-CHEMICAL (2018)
A Survey on Sensor Calibration in Air Pollution Monitoring Deployments
Balz Maag et al.
IEEE INTERNET OF THINGS JOURNAL (2018)
Informed Nonnegative Matrix Factorization Methods for Mobile Sensor Network Calibration
Clement Dorffer et al.
IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS (2018)
A Survey on Data Imputation Techniques: Water Distribution System as a Use Case
Muhammad S. Osman et al.
IEEE ACCESS (2018)
A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring
Naomi Zimmerman et al.
ATMOSPHERIC MEASUREMENT TECHNIQUES (2018)
Long-term evaluation of air sensor technology under ambient conditions in Denver, Colorado
Stephen Feinberg et al.
ATMOSPHERIC MEASUREMENT TECHNIQUES (2018)
End-user perspective of low-cost sensors for outdoor air pollution monitoring
Aakash C. Rai et al.
SCIENCE OF THE TOTAL ENVIRONMENT (2017)
Machine Learning-Based Calibration of Low-Cost Air Temperature Sensors Using Environmental Data
Kyosuke Yamamoto et al.
SENSORS (2017)
Electrochemical ozone sensors: A miniaturised alternative for ozone measurements in laboratory experiments and air-quality monitoring
Xiaobing Pang et al.
SENSORS AND ACTUATORS B-CHEMICAL (2017)
Field calibration of a cluster of low-cost commercially available sensors for air quality monitoring. Part B: NO, CO and CO2
Laurent Spinelle et al.
SENSORS AND ACTUATORS B-CHEMICAL (2017)
Community Air Sensor Network (CAIRSENSE) project: evaluation of low-cost sensor performance in a suburban environment in the southeastern United States
Wan Jiao et al.
ATMOSPHERIC MEASUREMENT TECHNIQUES (2016)
Hybrid prediction model with missing value imputation for medical data
Archana Purwar et al.
EXPERT SYSTEMS WITH APPLICATIONS (2015)
Field calibration of a cluster of low-cost available sensors for air quality monitoring. Part A: Ozone and nitrogen dioxide
Laurent Spinelle et al.
SENSORS AND ACTUATORS B-CHEMICAL (2015)
Deriving high-resolution urban air pollution maps using mobile sensor nodes
David Hasenfratz et al.
PERVASIVE AND MOBILE COMPUTING (2015)
A practical comparison of single and multiple imputation methods to handle complex missing data in air quality datasets
M. P. Gomez-Carracedo et al.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2014)
A new online data imputation method based on general regression auto associative neural network
Vadlamani Ravi et al.
NEUROCOMPUTING (2014)
Sequential Error Concealment for Video/Images by Sparse Linear Prediction
Jan Koloda et al.
IEEE TRANSACTIONS ON MULTIMEDIA (2013)
Multiple imputation using chained equations for missing data in TIMSS: a case study
Donia Smaali Bouhlila et al.
LARGE-SCALE ASSESSMENTS IN EDUCATION (2013)
The prevention and handling of the missing data
Hyun Kang
KOREAN JOURNAL OF ANESTHESIOLOGY (2013)
MissForest-non-parametric missing value imputation for mixed-type data
Daniel J. Stekhoven et al.
BIOINFORMATICS (2012)
Multiple imputation by chained equations: what is it and how does it work?
Melissa J. Azur et al.
INTERNATIONAL JOURNAL OF METHODS IN PSYCHIATRIC RESEARCH (2011)
Missing Data Analysis: Making It Work in the Real World
John W. Graham
ANNUAL REVIEW OF PSYCHOLOGY (2009)
CO, NO2 and NOx urban pollution monitoring with on-field calibrated electronic nose by automatic bayesian regularization
Saverio De Vito et al.
SENSORS AND ACTUATORS B-CHEMICAL (2009)
On field calibration of an electronic nose for benzene estimation in an urban pollution monitoring scenario
S. De Vito et al.
SENSORS AND ACTUATORS B-CHEMICAL (2008)
How many imputations are really needed? - Some practical clarifications of multiple imputation theory
John W. Graham et al.
PREVENTION SCIENCE (2007)
Data mining and the impact of missing data
ML Brown et al.
INDUSTRIAL MANAGEMENT & DATA SYSTEMS (2003)