Deep Gated Recurrent and Convolutional Network Hybrid Model for Univariate Time Series Classification
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2019, Vol 10, Issue 5
Abstract
Hybrid LSTM-fully convolutional networks (LSTM-FCN) for time series classification have produced state-of-the-art classification results on univariate time series. We empirically show that replacing the LSTM with a gated recurrent unit (GRU) to create a GRU-fully convolutional network hybrid model (GRU-FCN) can offer even better performance on many time series datasets without further changes to the model. Our empirical study showed that the proposed GRU-FCN model also outperforms the state-of-the-art classification performance in many univariate time series datasets without additional supporting algorithms requirement. Furthermore, since the GRU uses simpler architecture than the LSTM, it has fewer training parameters, less training time, smaller memory storage requirements, and simpler hardware implementation, compared to the LSTM-based models.
Authors and Affiliations
Nelly Elsayed, Anthony S Maida, Magdy Bayoumi
Keywords
Related Articles
- EP ID EP579357
- DOI 10.14569/IJACSA.2019.0100582
- Views 99
- Downloads 0
A Fresnelet-Based Encryption of Medical Images using Arnold Transform
Medical images are commonly stored in digital media and transmitted via Internet for certain uses. If a medical information image alters, this can lead to a wrong diagnosis which may create a serious health problem. More...
Detection and Identification System of Bacteria and Bacterial Endotoxin Based on Raman Spectroscopy
Sepsis is a global health problem that causes risk of death. In the developing world, about 60 to 80 % of death cases are caused by Sepsis. Rapid methods for detecting its causes, represent one of the major factors that...
Classifying three Communities of Assam Based on Anthropometric Characteristics using R Programming
The study of anthropometric characteristics of different communities plays an important role in design, ergonomics and architecture. As the change of life style, nutrition and ethnic composition of different communities...
Optical Recognition of Isolated Machine Printed Sindhi Characters using Fourier Descriptors
The scale invariance characteristics play an essential role in pattern recognition applications, for example in computer vision, OCR (Optical Character Recognition), electronic publication, etc. In this paper, the shape...
Detection of Mass Panic using Internet of Things and Machine Learning
The increase of emergency situations that cause mass panic in mass gatherings, such as terrorist attacks, random shooting, stampede, and fires, sheds light on the fact that advancements in technology should contribute in...