An Approach towards Missing Data Recovery within IoT Smart System
| Autor: | Khrystyna Zub, Natalia Kryvinska, Ivan Izonin, Roman Tkachenko |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Smart system
Mean squared error Computer science 020206 networking & telecommunications 02 engineering and technology Missing data computer.software_genre 0202 electrical engineering electronic engineering information engineering Decomposition (computer science) General Earth and Planetary Sciences 020201 artificial intelligence & image processing Data mining AdaBoost computer General Environmental Science Curse of dimensionality |
| Zdroj: | Procedia Computer Science. 155:11-18 |
| ISSN: | 1877-0509 |
| Popis: | Today, the fast development of the hardware for the Internet of things systems creates conditions for the development of IoT based Services of various purposes. The imperfect systems of collecting, aggregation and the transmission of large volumes of various types of data, fixed by sensors of IoT devices, as well as possible failures of the latter, cause the occurrence of missing data problems. The paper proposes a regression approach to solving the task of missed data recovery. The authors have developed a composition of the method of the missing data recovery for IoT systems based on the use of the Ito decomposition and the AdaBoost algorithm. We transform each data vectors by using Ito decomposition, and searching the coefficients of this decomposition scheme using AdaBoost algorithm. Increasing the dimensionality of the input space due to the use of the second-degree Ito decomposition scheme, as well as its high approximation properties, allowed to increase the accuracy of filling the missed values by the AdaBoost regressor at more than 6% (MAPE). It has been established that the developed method provides the highest accuracy of filling missed data based on all other indicators (MAE, RMSE, SMAPE) among the considered regression methods. |
| Databáze: | OpenAIRE |
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