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 257
- Downloads 0
Proof-of-Concept System for Opportunistic Spectrum Access in Multi-user Decentralized Networks
Poor utilization of an electromagnetic spectrum and ever increasing demand for spectrum have led to surge of interests in opportunistic spectrum access (OSA) based paradigms like cognitive radio and unlicensed LTE. In OS...
Miniaturized Implantable DS-PIFA Antenna for Biomedical Applications
This paper presents an implantable miniaturized planar inverted-F antenna (PIFA) for biomedical applications. We propose small sized PIFA that can operate over 2.45 GHz Industrial, Scientific, and Medical (ISM) band. We...
Optimal Random Access and Random Spectrum Sensing for an Energy Harvesting Cognitive Radio with and without Primary Feedback Leveraging
We consider a secondary user (SU) with energy harvesting capability. We design access schemes for the SU which incorporate random spectrum sensing and random access, and which make use of the primary automatic repeat req...
A Method for Detecting Damage of Traffic Marks by Half Celestial Camera Attached to Cars
Roads are becoming deterioration in everywhere. In some places, traffic marks painted on roads are damaged thus needed to be updated. Municipalities must manage road condition and traffic marks (road painting). It is the...
A Life Extend Approach Based on Priority Queue N Strategy for Wireless Sensor Network
In this paper, we proposed a method on the tradeoff between packet transmission speed and battery life in wireless sensor networks (WSN). The data obtained by sensor nodes comprised various types of information with vari...