论文信息 - Interpolation of Missing Data in Sensor Networks Using Nonnegative Matrix Factorization

Interpolation of Missing Data in Sensor Networks Using Nonnegative Matrix Factorization

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.

Hiroshi Sawada | Yasue Kishino | Yoshinari Shirai | Takayuki Suyama | Shin Mizutani

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