K-Nearest Neighbor Based Missing Data Estimation Algorithm in Wireless Sensor Networks

Journals Menu

Follow SCIRP

	+1 323-425-8868
	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Wireless Sensor Network

ISSN Print: 1945-3078
ISSN Online: 1945-3086
www.scirp.org/journal/wsn
E-mail: wsn@scirp.org

Google-based Impact Factor: 1
Citations h5-index & Ranking*

Journals Menu

"K-Nearest Neighbor Based Missing Data Estimation Algorithm in Wireless Sensor Networks"
written by Liqiang Pan, Jianzhong Li,
published by Wireless Sensor Network, Vol.2 No.2, 2010

has been cited by the following article(s):

Google Scholar
CrossRef

[1]	Causal Feature Selection with Missing Data
	… Transactions on Knowledge Discovery from Data …, 2022

[2]	Evaluation of Odor Prediction Model Performance and Variable Importance according to Various Missing Imputation Methods
	Applied Sciences, 2022

[3]	A Survey of Sparse Mobile Crowdsensing: Developments and Opportunities
	IEEE Open Journal of the …, 2022

[4]	Recovery Algorithm of Power Metering Data Based on Collaborative Fitting
	Energies, 2022

[5]	Critical Comparison of Data Imputation Techniques at IoT Edge
	International Symposium on …, 2022

[6]	DA-Bi-SRU for water quality prediction in smart mariculture
	Computers and Electronics in …, 2022

[7]	Link quality estimation based on over-sampling and weighted random forest
	Computer Science and Information …, 2022

[8]	Online Missing Data Imputation Using Virtual Temporal Neighbor in Wireless Sensor Networks
	Wireless Communications and …, 2022

[9]	Spatial epidemiology of diseases of the nervous system: A Machine Learning approach
	2021

[10]	Impacts of missing data in risk management
	2021

[11]	Enabling Reliable and Efficient Data Transfer for Internet of Things Applications
	2021

[12]	A Recursive Method for Estimating Missing Data in Spatio-Temporal Applications
	IEEE Transactions on Industrial Informatics, 2021

[13]	Missing Data Reconstruction Based on Spectral k-Support Norm Minimization for NB-IoT Data
	Mathematical Problems in Engineering, 2021

[14]	Temporal and spatial nearest neighbor values based missing data imputation in wireless sensor networks
	2021

[15]	Cost-Effective Active Sparse Urban Sensing: An Adversarial Auto-Encoder Approach
	2021

[16]	To Tolerate or To Impute Missing Values in V2X Communications Data?
	2021

[17]	A Missing Type-Aware Adaptive Interpolation Framework for Sensor Data
	IEEE Transactions on …, 2021

[18]	Embedded Data Imputation for Environmental Intelligent Sensing: A Case Study
	Sensors, 2021

[19]	Missing Data Inference for Crowdsourced Radio Map Construction: An Adversarial Auto-Encoder Method
	2021

[20]	A New Regularized Recursive Dynamic Factor Analysis with Variable Forgetting Factor and Subspace Dimension for Wireless Sensor Networks with Missing Data
	2021

[21]	Missing Value Imputation for Multi-view Urban Statistical Data via Spatial Correlation Learning
	2021

[22]	iDEG: integrated data and energy gathering for wireless systems
	2021

[23]	Network-wide Spatio-Temporal Predictive Learning for the Intelligent Transportation System
	2020

[24]	Missing Data Imputation with Bayesian Maximum Entropy for Internet of Things Applications
	2020

[25]	Smart Sensing for Container Trucks
	2020

[26]	Thirty years of machine learning: The road to Pareto-optimal wireless networks
	2020

[27]	A method overview in smart aquaculture
	2020

[28]	Sequence Imputation using Machine Learning with Early Stopping Mechanism
	2020

[29]	Introducing Machine Learning to Wireless Sensor Networks: Requirements and Applications
	2020

[30]	Runtime Control of LoRa Spreading Factor for Campus Shuttle Monitoring
	2020

[31]	EGCIR: Energy-Aware Graph Clustering and Intelligent Routing Using Supervised System in Wireless Sensor Networks
	2020

[32]	A Spatial Missing Value Imputation Method for Multi-view Urban Statistical Data
	2020

[33]	Multivariable data imputation for the analysis of incomplete credit data
	2020

[34]	Automatic Thresholding for Sensor Data Gap Detection Using Statistical Approach
	2020

[35]	Imputing Block of Missing Data Using Deep Autoencoder
	2020

[36]	Combining multiple imputation and control function methods to deal with missing data and endogeneity in discrete-choice models
	2020

[37]	Machines' Fault Detection and Tolerance Using Big Data Management
	2019

[38]	IoT Data Validation Using Spatial and Temporal Correlations
	2019

[39]	Missing value imputation using a novel grey based fuzzy c-means, mutual information based feature selection, and regression model
	Expert Systems with Applications, 2019

[40]	Correlation Analysis and Statistical Characterization of Heterogeneous Sensor Data in Environmental Sensor Networks
	2019

[41]	Energy-efficient data gathering algorithm relying on compressive sensing in lossy WSNs
	2019

[42]	Ensuring analyzing and monetization of data using data science and blockchain in loT devices
	2019

[43]	Energy-Efficient Approximate Data Collection and BP-Based Reconstruction in UWSNs
	2019

[44]	Robust Distributed Parameter Estimation of Nonlinear Systems with Missing Data over Networks
	2019

[45]	iDEG: Integrated Data and Energy Gathering Framework for Practical Wireless Sensor Networks Using Compressive Sensing
	2019

[46]	Thirty Years of Machine Learning: The Road to Pareto-Optimal Next-Generation Wireless Networks
	2019

[47]	Privacy-aware Controllable Compressed Data Publishing against Sparse Estimation Attack in Internet of Things
	2019

[48]	Increasing The Precision Of Noise Source Detection System using KNN Method
	2019

[49]	An RNN-based Delay-guaranteed Monitoring Framework in Underwater Wireless Sensor Networks
	2019

[50]	Machine Learning Algorithms and Fault Detection for Improved Belief Function Based Decision Fusion in Wireless Sensor Networks
	2019

[51]	Profiling-Based Classification Algorithms for Security Applications in Internet of Things
	2019

[52]	A Study of Simple Partially-Recovered Sensor Data Imputation Methods
	2019

[53]	diagnosis in building: new challenges
	2019

[54]	Denoising Recurrent Neural Networks for Classifying Crash-Related Events
	2019

[55]	Correlation Analysis of Multimodal Sensor Data in Environmental Sensor Networks
	2019

[56]	A Review of Missing Sensor Data Imputation Methods
	2019

[57]	Εξόρυξη δεδομένων στο διαδίκτυο των πραγμάτων
	2019

[58]	diagnostic du système bâtiment: nouveaux défis
	2019

[59]	Sampling, qualification and analysis of data streams
	2018

[60]	PCI-MDR: Missing Data Recovery in Wireless Sensor Networks using Partial Canonical Identity Matrix
	2018

[61]	Privacy-aware data publishing against sparse estimation attack
	Journal of Network and Computer Applications, 2018

[62]	Deep Learning of Virtual Marine Sensors
	Dissertation, 2018

[63]	Multi-attribute Missing Data Reconstruction Based on Adaptive Weighted Nuclear Norm Minimization in IoT
	2018

[64]	Reconstruction of Missing Big Sensor Data
	2017

[65]	An Agricultural Sensor Data Recovering Method Based on Matrix Completion Theory
	2017

[66]	Missing value estimation for microarray data through cluster analysis
	Knowledge and Information Systems, 2017

[67]	Predicting Missing Values in Wireless Sensor Network using Spatial-Temporal Correlation
	2017

[68]	Missing Data Estimation Algorithm Based on Temporal Correlation in Wireless Sensor Networks
	2017

[69]	Interpolating the Missing Values for Multi-Dimensional Spatial-Temporal Sensor Data: A Tensor SVD Approach
	2017

[70]	A new regularized recursive dynamic factor analysis with variable forgetting factor for wireless sensor networks with missing data
	2017

[71]	Recover Missing Sensor Data with Iterative Imputing Network
	2017

[72]	kNN ensembles with penalized DTW for multivariate time series imputation
	2016

[73]	无线传感器网络中基于灰色关联度的丢失数据估算算法
	福建电脑, 2016

[74]	ST-MVL: Filling Missing Values in Geo-sensory Time Series Data
	2016

[75]	Missing data: On criteria to evaluate imputation methods
	2016

[76]	Восстановление пропущенных значений в разнородных шкалах с большим числом пропусков
	Machine Learning, 2015

[77]	A benchmark for spatial and temporal correlation based data prediction in wireless sensor networks
	Intelligent Systems: Theories and Applications (SITA), 2015 10th International Conference on, 2015

[78]	基于属性相关性的无线传感网络缺失数据估计方法
	计算机应用, 2015

[79]	Coverage Aware Scheduling in Wireless Sensor Networks: An Optimal Placement Approach
	Wireless Personal Communications, 2015

[80]	基于属性相关性的无线传感网络缺失值估计方法
	2015

[81]	Recommending missing sensor values
	2015

[82]	Using temporal correlation and time series to detect missing activity-driven sensor events
	2015

[83]	An Optimal Linear Predictive Model for Missing Data Estimation in Wireless Sensor Network
	International Journal of Innovative Research in Computer and Communication Engineering, 2015

[84]	核电厂环境辐射监测传感器网络中缺失值的粒子群算法-最小二乘支持向量机估计算法
	核电子学与探测技术, 2014

[85]	Determining missing values in dimension incomplete databases using spatial-temporal correlation techniques
	Advanced Communication Control and Computing Technologies (ICACCCT), 2014 International Conference, 2014

[86]	No-sense: Sense with dormant sensors
	Communications (NCC), 2014 Twentieth National Conference on. IEEE, 2014

[87]	A GS-MPSO-WKNN method for missing data imputation in wireless sensor networks monitoring manufacturing conditions
	Transactions of the Institute of Measurement and Control, 2014

[88]	CIAM: An adaptive 2-in-1 missing data estimation algorithm in wireless sensor networks
	Networks (ICON), 2013 19th IEEE International Conference on. IEEE, 2013

[89]	A Hybrid Approach for Improving the Data Quality of Mobile Phone Sensing
	International Journal of Distributed Sensor Networks.Hindawi Publishing Corporation , 2013

[90]	An Estimation Model of Missing Data for Smart Phone Sensing
	??????????? ???, 2013

[91]	Model-based Transmission Reduction and Virtual Sensing in Wireless Sensor Networks
	Thesis, 2013

[92]	农业物联网应用发展研究
	广东农业科学, 2013

[93]	스마트폰 센싱을 위한 손실 데이터 추정 모델
	2013

[94]	物联网信息感知与交互技术
	计算机学报, 2012

[95]	基于 SVM 的核电站环境辐射监测网络中传感器节点缺失值估计算法
	南华大学学报: 自然科学版, 2012

[96]	Dispersion–based prediction framework for estimating missing values in wireless sensor networks
	International Journal of Sensor Networks, 2012

[97]	Collaborative estimation of environmental parameters
	Proceedings of the 11th WSEAS international conference on Instrumentation, Measurement, Circuits and Systems, and Proceedings of, 2012

[98]	LSSVM based missing data imputation in nuclear power plant's environmental radiation monitor sensor network
	Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on. IEEE, 2012

[1]	Deep Compressed Sensing based Data Imputation for Urban Environmental Monitoring ACM Transactions on Sensor Networks, 2024 DOI:10.1145/3599236

[2]	Vehicular Crowdsensing Inference and Prediction With Multi Training Graph Transformer Networks IEEE Internet of Things Journal, 2024 DOI:10.1109/JIOT.2023.3305006

[3]	Temporal rainfall variability and drought characterization in Cheleka Watershed, Awash River Basin, Ethiopia Journal of Hydrology: Regional Studies, 2024 DOI:10.1016/j.ejrh.2024.101663

[4]	Missing signal imputation for multi-channel sensing signals on rotary machinery by tensor factorization Manufacturing Letters, 2023 DOI:10.1016/j.mfglet.2023.08.097

[5]	Deep probabilistic graphical modeling for robust multivariate time series anomaly detection with missing data Reliability Engineering & System Safety, 2023 DOI:10.1016/j.ress.2023.109410

[6]	Constraint Decision-Making Systems in Engineering Advances in Computational Intelligence and Robotics, 2023 DOI:10.4018/978-1-6684-7343-6.ch006

[7]	Causal Feature Selection with Missing Data ACM Transactions on Knowledge Discovery from Data, 2022 DOI:10.1145/3488055

[8]	Link quality estimation based on over-sampling and weighted random forest Computer Science and Information Systems, 2022 DOI:10.2298/CSIS201218041L

[9]	DA-Bi-SRU for water quality prediction in smart mariculture Computers and Electronics in Agriculture, 2022 DOI:10.1016/j.compag.2022.107219

[10]	Long Gaps Missing IoT Sensors Time Series Data Imputation: A Bayesian Gaussian Approach IEEE Access, 2022 DOI:10.1109/ACCESS.2022.3218785

[11]	Imputation of Missing PM2.5 Observations in a Network of Air Quality Monitoring Stations by a New kNN Method Atmosphere, 2022 DOI:10.3390/atmos13111934

[12]	Advanced Data Mining and Applications Lecture Notes in Computer Science, 2022 DOI:10.1007/978-3-031-22064-7_24

[13]	A Recursive Method for Estimating Missing Data in Spatio-Temporal Applications IEEE Transactions on Industrial Informatics, 2022 DOI:10.1109/TII.2021.3100501

[14]	Causal Feature Selection with Missing Data ACM Transactions on Knowledge Discovery from Data, 2022 DOI:10.1145/3488055

[15]	Online Missing Data Imputation Using Virtual Temporal Neighbor in Wireless Sensor Networks Wireless Communications and Mobile Computing, 2022 DOI:10.1155/2022/4909476

[16]	Recovery Algorithm of Power Metering Data Based on Collaborative Fitting Energies, 2022 DOI:10.3390/en15041570

[17]	Evaluation of Odor Prediction Model Performance and Variable Importance according to Various Missing Imputation Methods Applied Sciences, 2022 DOI:10.3390/app12062826

[18]	Intelligent Distributed Computing XIV Studies in Computational Intelligence, 2022 DOI:10.1007/978-3-030-96627-0_4

[19]	To Tolerate or To Impute Missing Values in V2X Communications Data? IEEE Internet of Things Journal, 2022 DOI:10.1109/JIOT.2021.3126749

[20]	A Survey of Sparse Mobile Crowdsensing: Developments and Opportunities IEEE Open Journal of the Computer Society, 2022 DOI:10.1109/OJCS.2022.3177290

[21]	A Survey of Sparse Mobile Crowdsensing: Developments and Opportunities IEEE Open Journal of the Computer Society, 2022 DOI:10.1109/OJCS.2022.3177290

[22]	To Tolerate or To Impute Missing Values in V2X Communications Data? IEEE Internet of Things Journal, 2022 DOI:10.1109/JIOT.2021.3126749

[23]	MTTPRE Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 2022 DOI:10.1145/3557915.3560986

[24]	MTTPRE Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 2022 DOI:10.1145/3557915.3560986

[25]	DA-Bi-SRU for water quality prediction in smart mariculture Computers and Electronics in Agriculture, 2022 DOI:10.1016/j.compag.2022.107219

[26]	DA-Bi-SRU for water quality prediction in smart mariculture Computers and Electronics in Agriculture, 2022 DOI:10.1016/j.compag.2022.107219

[27]	DA-Bi-SRU for water quality prediction in smart mariculture Computers and Electronics in Agriculture, 2022 DOI:10.1016/j.compag.2022.107219

[28]	Missing Value Imputation for Multi-view Urban Statistical Data via Spatial Correlation Learning IEEE Transactions on Knowledge and Data Engineering, 2021 DOI:10.1109/TKDE.2021.3072642

[29]	Missing Data Imputation With Bayesian Maximum Entropy for Internet of Things Applications IEEE Internet of Things Journal, 2021 DOI:10.1109/JIOT.2020.2987979

[30]	International Conference on Mobile Computing and Sustainable Informatics EAI/Springer Innovations in Communication and Computing, 2021 DOI:10.1007/978-3-030-49795-8_66

[31]	Temporal and Spatial Nearest Neighbor Values Based Missing Data Imputation in Wireless Sensor Networks Sensors, 2021 DOI:10.3390/s21051782

[32]	Missing Data Inference for Crowdsourced Radio Map Construction: An Adversarial Auto-Encoder Method 2021 IEEE Wireless Communications and Networking Conference (WCNC), 2021 DOI:10.1109/WCNC49053.2021.9417253

[33]	A New Regularized Recursive Dynamic Factor Analysis With Variable Forgetting Factor and Subspace Dimension for Wireless Sensor Networks With Missing Data IEEE Transactions on Instrumentation and Measurement, 2021 DOI:10.1109/TIM.2021.3083889

[34]	Cost-Effective Active Sparse Urban Sensing: Adversarial Autoencoder Approach IEEE Internet of Things Journal, 2021 DOI:10.1109/JIOT.2021.3060815

[35]	A Missing Type-Aware Adaptive Interpolation Framework for Sensor Data IEEE Transactions on Instrumentation and Measurement, 2021 DOI:10.1109/TIM.2021.3089783

[36]	Missing Data Reconstruction Based on Spectral k-Support Norm Minimization for NB-IoT Data Mathematical Problems in Engineering, 2021 DOI:10.1155/2021/1336900

[37]	Embedded Data Imputation for Environmental Intelligent Sensing: A Case Study Sensors, 2021 DOI:10.3390/s21237774

[38]	Runtime Control of LoRa Spreading Factor for Campus Shuttle Monitoring 2020 IEEE 28th International Conference on Network Protocols (ICNP), 2020 DOI:10.1109/ICNP49622.2020.9259383

[39]	Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks Advances in Information Security, Privacy, and Ethics, 2020 DOI:10.4018/978-1-7998-5068-7.ch001

[40]	A method overview in smart aquaculture Environmental Monitoring and Assessment, 2020 DOI:10.1007/s10661-020-08409-9

[41]	Sustainability in Energy and Buildings Smart Innovation, Systems and Technologies, 2020 DOI:10.1007/978-981-32-9868-2_39

[42]	Robust Distributed Parameter Estimation of Nonlinear Systems With Missing Data Over Networks IEEE Transactions on Aerospace and Electronic Systems, 2020 DOI:10.1109/TAES.2019.2948515

[43]	Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks IEEE Communications Surveys & Tutorials, 2020 DOI:10.1109/COMST.2020.2965856

[44]	EGCIR: Energy-Aware Graph Clustering and Intelligent Routing Using Supervised System in Wireless Sensor Networks Energies, 2020 DOI:10.3390/en13164072

[45]	Smart Sensing for Container Trucks 2020 6th International Conference on Big Data Computing and Communications (BIGCOM), 2020 DOI:10.1109/BigCom51056.2020.00007

[46]	Sequence Imputation using Machine Learning with Early Stopping Mechanism 2020 International Conference on Computational Performance Evaluation (ComPE), 2020 DOI:10.1109/ComPE49325.2020.9200099

[47]	Combining multiple imputation and control function methods to deal with missing data and endogeneity in discrete-choice models Transportation Research Part B: Methodological, 2020 DOI:10.1016/j.trb.2020.10.002

[48]	Multivariable data imputation for the analysis of incomplete credit data Expert Systems with Applications, 2020 DOI:10.1016/j.eswa.2019.112926

[49]	Denoising Recurrent Neural Networks for Classifying Crash-Related Events IEEE Transactions on Intelligent Transportation Systems, 2020 DOI:10.1109/TITS.2019.2921722

[50]	An RNN-Based Delay-Guaranteed Monitoring Framework in Underwater Wireless Sensor Networks IEEE Access, 2019 DOI:10.1109/ACCESS.2019.2899916

[51]	iDEG: Integrated Data and Energy Gathering Framework for Practical Wireless Sensor Networks Using Compressive Sensing IEEE Sensors Journal, 2019 DOI:10.1109/JSEN.2018.2878788

[52]	A Study of Simple Partially-Recovered Sensor Data Imputation Methods 2019 15th International Conference on Network and Service Management (CNSM), 2019 DOI:10.23919/CNSM46954.2019.9012748

[53]	Correlation Analysis of Multimodal Sensor Data in Environmental Sensor Networks 2019 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), 2019 DOI:10.1109/ANTS47819.2019.9118157

[54]	Smart Computing and Communication Lecture Notes in Computer Science, 2019 DOI:10.1007/978-3-030-34139-8_10

[55]	Metadata and Semantic Research Communications in Computer and Information Science, 2019 DOI:10.1007/978-3-030-36599-8_7

[56]	A Review of Missing Sensor Data Imputation Methods 2019 5th International Conference on Science and Technology (ICST), 2019 DOI:10.1109/ICST47872.2019.9166287

[57]	Machine Learning Algorithms and Fault Detection for Improved Belief Function Based Decision Fusion in Wireless Sensor Networks Sensors, 2019 DOI:10.3390/s19061334

[58]	PCI-MDR: Missing Data Recovery in Wireless Sensor Networks Using Partial Canonical Identity Matrix IEEE Wireless Communications Letters, 2019 DOI:10.1109/LWC.2018.2882403

[59]	Energy-efficient data gathering algorithm relying on compressive sensing in lossy WSNs Measurement, 2019 DOI:10.1016/j.measurement.2019.106875

[60]	Privacy-Aware Controllable Compressed Data Publishing Against Sparse Estimation Attack in IoT IEEE Internet of Things Journal, 2019 DOI:10.1109/JIOT.2019.2916109

[61]	Profiling-Based Classification Algorithms for Security Applications in Internet of Things 2019 IEEE International Congress on Internet of Things (ICIOT), 2019 DOI:10.1109/ICIOT.2019.00033

[62]	Correlation analysis and statistical characterization of heterogeneous sensor data in environmental sensor networks Computer Networks, 2019 DOI:10.1016/j.comnet.2019.106902

[63]	Privacy-aware data publishing against sparse estimation attack Journal of Network and Computer Applications, 2018 DOI:10.1016/j.jnca.2018.02.016

[64]	Missing value imputation using a novel grey based fuzzy c-means, mutual information based feature selection, and regression model Expert Systems with Applications, 2018 DOI:10.1016/j.eswa.2018.07.057

[65]	Multi-Attribute Missing Data Reconstruction Based on Adaptive Weighted Nuclear Norm Minimization in IoT IEEE Access, 2018 DOI:10.1109/ACCESS.2018.2876701

[66]	A new regularized recursive dynamic factor analysis with variable forgetting factor for wireless sensor networks with missing data 2017 IEEE International Symposium on Circuits and Systems (ISCAS), 2017 DOI:10.1109/ISCAS.2017.8050594

[67]	Interpolating the Missing Values for Multi-Dimensional Spatial-Temporal Sensor Data Proceedings of the 14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, 2017 DOI:10.1145/3144457.3144474

[68]	kNN ensembles with penalized DTW for multivariate time series imputation 2016 International Joint Conference on Neural Networks (IJCNN), 2016 DOI:10.1109/IJCNN.2016.7727549

[69]	A benchmark for spatial and temporal correlation based data prediction in wireless sensor networks 2015 10th International Conference on Intelligent Systems: Theories and Applications (SITA), 2015 DOI:10.1109/SITA.2015.7358441

[70]	Coverage Aware Scheduling in Wireless Sensor Networks: An Optimal Placement Approach Wireless Personal Communications, 2015 DOI:10.1007/s11277-015-2862-8

[71]	Using temporal correlation and time series to detect missing activity-driven sensor events 2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops), 2015 DOI:10.1109/PERCOMW.2015.7133991

[72]	Recommending missing sensor values 2015 IEEE International Conference on Big Data (Big Data), 2015 DOI:10.1109/BigData.2015.7363779

[73]	Determining missing values in dimension incomplete databases using spatial-temporal correlation techniques 2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies, 2014 DOI:10.1109/ICACCCT.2014.7019157

[74]	No-sense: Sense with dormant sensors 2014 Twentieth National Conference on Communications (NCC), 2014 DOI:10.1109/NCC.2014.6811303

[75]	A GS-MPSO-WKNN method for missing data imputation in wireless sensor networks monitoring manufacturing conditions Transactions of the Institute of Measurement and Control, 2014 DOI:10.1177/0142331214534291

[76]	An Estimation Model of Missing Data for Smart Phone Sensing The Journal of the Institute of Webcasting, Internet and Telecommunication, 2013 DOI:10.7236/JIIBC.2013.13.3.33

[77]	A Hybrid Approach for Improving the Data Quality of Mobile Phone Sensing International Journal of Distributed Sensor Networks, 2013 DOI:10.1155/2013/786594

[78]	CIAM: An adaptive 2-in-1 missing data estimation algorithm in wireless sensor networks 2013 19th IEEE International Conference on Networks (ICON), 2013 DOI:10.1109/ICON.2013.6781986

[79]	LSSVM based missing data imputation in nuclear power plant's environmental radiation monitor sensor network 2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI), 2012 DOI:10.1109/ICACI.2012.6463210

[80]	Particle Swarm Optimization Least Square Support Machine Based Missing Data Imputation Algorithm in Wireless Sensor Network for Nuclear Power Plant’s Environmental Radiation Monitor Advanced Materials Research, 2012 DOI:10.4028/www.scientific.net/AMR.605-607.2137

Follow SCIRP

	+1 323-425-8868
	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Wireless Sensor Network

Wireless Sensor Network

Journals Menu

Home

About SCIRP

Service

Policies