scholarly journals Time Series Data Analysis of Wireless Sensor Network Measurements of Temperature

Sensors ◽  
2017 ◽  
Vol 17 (6) ◽  
pp. 1221 ◽  
Author(s):  
Siddhartha Bhandari ◽  
Neil Bergmann ◽  
Raja Jurdak ◽  
Branislav Kusy
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Time Series Data ◽  
Wireless Sensor ◽  
Series Data ◽  
Network Measurements ◽  
Time Series Data Analysis

Outlier Detection Using Convolutional Neural Network for Wireless Sensor Network

2021 ◽  
Vol 17 (2) ◽  
pp. 0-0
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Deep Learning ◽  
Wireless Sensor Network ◽  
Convolutional Neural Network ◽  
Sensor Network ◽  
Time Series Data ◽  
Wireless Sensor ◽  
Series Data ◽  
Detection Accuracy

Over the recent years, the term deep learning has been considered as one of the primary choice for handling huge amount of data. Having deeper hidden layers, it surpasses classical methods for detection of outlier in wireless sensor network. The Convolutional Neural Network (CNN) is a biologically inspired computational model which is one of the most popular deep learning approaches. It comprises neurons that self-optimize through learning. EEG generally known as Electroencephalography is a tool used for investigation of brain function and EEG signal gives time-series data as output. In this paper, we propose a state-of-the-art technique designed by processing the time-series data generated by the sensor nodes stored in a large dataset into discrete one-second frames and these frames are projected onto a 2D map images. A convolutional neural network (CNN) is then trained to classify these frames. The result improves detection accuracy and encouraging.

Examining the Long Run Effects of Export, Import and FDI Inflows on the FDI Outflows from India: A Causality Analysis

2009 ◽  
Vol 10 (1) ◽  
pp. 65-88
Author(s):  
Nandita Dasgupta
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Driving Force ◽  
Time Series Data ◽  
Series Data ◽  
Causality Analysis ◽  
Fdi Inflows ◽  
Long Run ◽  
Time Series Data Analysis ◽  
Trade And Investment

The objective of this paper is to examine the effects of international trade and investment related macro economic variables, namely, exports, imports and FDI inflows on the outflows of FDI from India over 1970 through 2005. Using time series data analysis, the empirical part of the paper finds unidirectional Granger Causality from export and import to FDI outflows but no such causality exists from FDI inflows to the corresponding outflows from India. Results confirm the assumption that lagged imports and exports are a driving force of ing front.

scholarly journals Periodic Time Series Data Analysis by Deep Learning Methodology

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 223078-223088
Author(s):  
Haolong Zhang ◽  
Haoye Lu ◽  
Amiya Nayak
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Data Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Periodic Time Series ◽  
Time Series Data Analysis

Robust Extrema Features for Time-Series Data Analysis

2013 ◽  
Vol 35 (6) ◽  
pp. 1464-1479 ◽  
Author(s):  
Pramod K. Vemulapalli ◽  
Vishal Monga ◽  
Sean N. Brennan
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Time Series Data Analysis

scholarly journals Efficient Methods for Calculating Sample Entropy in Time Series Data Analysis

2018 ◽  
Vol 145 ◽  
pp. 97-104 ◽  
Author(s):  
Ronakben Bhavsar ◽  
Na Helian ◽  
Yi Sun ◽  
Neil Davey ◽  
Tony Steffert ◽  
...  
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Time Series Data ◽  
Sample Entropy ◽  
Series Data ◽  
Time Series Data Analysis
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