Interpolation of Missing Data in Sensor Networks Using Nonnegative Matrix Factorization

被引：2

作者：

Suyama, Takayuki ^{[1
]}

Kishino, Yasue ^{[1
]}

Shirai, Yoshinari ^{[1
]}

Mizutani, Shin ^{[1
]}

Sawada, Hiroshi ^{[1
]}

机构：

[1] NTT Commun Sci Labs, 2-4 Hikaridai, Seika, Kyoto 6190237, Japan

来源：

PROCEEDINGS OF THE 2018 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING AND PROCEEDINGS OF THE 2018 ACM INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTERS (UBICOMP/ISWC'18 ADJUNCT) | 2018年

关键词：

Sensor networks; Interpolation; Nonnegative Matrix Factorization;

D O I：

10.1145/3267305.3267585

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We propose a method that interpolates missing values from sensor nodes in a sensor network using Nonnegative Matrix Factorization. Since nearby sensor nodes take approximate values, more reliable interpolation is possible with these values. We carried out experiments and evaluations using the data of sensors deployed in a real environment.

引用

页码：263 / 266

页数：4