Time Series Forecasting with Missing Values
Journal Title: EAI Endorsed Transactions on Cognitive Communications - Year 2015, Vol 1, Issue 4
Abstract
Time series prediction has become more popular in various kinds of applications such as weather prediction, control engineering, financial analysis, industrial monitoring, etc. To deal with real-world problems, we are often faced with missing values in the data due to sensor malfunctions or human errors. Traditionally, the missing values are simply omitted or replaced by means of imputation methods. However, omitting those missing values may cause temporal discontinuity. Imputation methods, on the other hand, may alter the original time series. In this study, we propose a novel forecasting method based on least squares support vector machine (LSSVM). We employ the input patterns with the temporal information which is defined as local time index (LTI). Time series data as well as local time indexes are fed to LSSVM for doing forecasting without imputation. We compare the forecasting performance of our method with other imputation methods. Experimental results show that the proposed method is promising and is worth further investigations.
Authors and Affiliations
Shin-Fu Wu, Chia-Yung Chang, Shie-Jue Lee
Keywords
Related Articles
- EP ID EP45631
- DOI http://dx.doi.org/10.4108/icst.iniscom.2015.258269
- Views 223
- Downloads 0
On the Performance Analysis and Evaluation of Scaled Largest Eigenvalue in Spectrum Sensing: A Simple Form Approach
Scaled Largest Eigenvalue (SLE) detector stands out as the optimal single-primary-user detector in uncertain noisy environments. In this paper, we consider a multi-antenna cognitive radio system in which we aim at detect...
WiFi Localization Based on IEEE 802.11 RTS/CTS Mechanism
Location Based Services are providing one of the fastest growing market segments today. While the most common technique for location determination is GPS, several alternative approaches have been proposed for Wi-Fi envir...
Signal Interference Analysis Model In Near-Field Coupling Communication
Near-field coupling communication (NFCC) is a technology that uses the surface of the human body as a transmission path. To suppress the radiation signal from the human body, NFCC devices use a carrier frequency of less...
Detecting Multi-ChannelWireless Microphone User Emulation Attacks in White Space with Noise
Cognitive radio networks (CRNs) are susceptible to primary user emulation (PUE) attacks. Conventional PUE attack detection approaches consider television broadcasting as the primary user. In this work, however, we study...
TimeNET Optimization Environment
In this paper a novel tool for simulation-based optimization and design-space exploration of Stochastic Colored Petri nets (SCPN) is introduced. The working title of this tool is TimeNET Optimization Environment (TOE). T...