Estimating Missing Values of WSN using modified Frequent itemsets mining and NN search

DOI

10.2991/iccmcee-15.2015.120How to use a DOI?

Keywords

Wireless Sensor Network, Missing Data Imputation, Modified Frequent Itemsets Mining, Nearest Neighbor Estimation

Abstract

Due to causes such as unreliability of the transport protocol, energy exhaustion and noise disturbance etc in wireless sensor network, the uploaded data on the sensor node usually tend to be incomplete, which brings about a series of inconvenience for analysis and operation in the subsequent. Therefore, it is necessary for us to make compensation for the missing data. In this paper, we put forward one kind of method of combing with modified Frequent Itemsets mining and NN search(FINN) to make estimation for the missing data in the wireless sensor network and use estimated data to replace missing value. Because the final operation only uses similar data, it is unnecessary to use all the data, so it can reduce unnecessary error and enhance precision of estimated value.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - MengZhenfeng Luo
AU  - Fan Wang
AU  - Xiaopeng Hu
PY  - 2015/11
DA  - 2015/11
TI  - Estimating Missing Values of WSN using modified Frequent itemsets mining and NN search
BT  - Proceedings of the 2015 4th International Conference on Computer, Mechatronics, Control and Electronic Engineering
PB  - Atlantis Press
SP  - 666
EP  - 671
SN  - 2352-5401
UR  - https://doi.org/10.2991/iccmcee-15.2015.120
DO  - 10.2991/iccmcee-15.2015.120
ID  - Luo2015/11
ER  -