Results 41 to 50 of about 80,307 (206)

A New Time Series Representation Model and Corresponding Similarity Measure for Fast and Accurate Similarity Detection

IEEE Access, 2017
Data representation and similarity measurement are two basic aspects of similarity detection in time series data mining. In this paper, we present two novel approaches to perform similarity detection efficiently and effectively.
Miaomiao Zhang, Dechang Pi
doaj   +1 more source

Detecting anomalies in multivariate time series from automotive systems [PDF]

, 2013
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In the automotive industry test drives are conducted during the development of new vehicle models or as a part of quality assurance for series vehicles ...
Theissler, Andreas
core  

Combining Deep Neural Networks and Classical Time Series Regression Models for Forecasting Patient Flows in Hong Kong

IEEE Access, 2019
Deep Neural Networks (DNNs) has been dominating recent data mining related tasks with better performances. This article proposes a hybrid approach that exploits the unique predictive power of DNN and classical time series regression models, including ...
Shancheng Jiang, Ran Xiao, Long Wang, Xiong Luo, Chao Huang, Jenq-Haur Wang, Kwai-Sang Chin, Ximing Nie   +7 more
doaj   +1 more source

Spatiotemporal Data Mining Problems and Methods

Analytics, 2023
Many scientific fields show great interest in the extraction and processing of spatiotemporal data, such as medicine with an emphasis on epidemiology and neurology, geology, social sciences, meteorology, and a great interest is also observed in the study
Eleftheria Koutsaki, George Vardakis, Nikolaos Papadakis   +2 more
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Multiscale Average Absolute Difference (MSAAD): A Computationally Efficient and Nonparametric Adaptation of Line Length for Noisy, Uncontrolled Wearables Time Series

Algorithms
With the rise in physiological data sampled from wearable devices, efficient methods must be developed to encode temporal information for the comparison of time series arising from uncontrolled monitoring.
Jamison H. Burks, Wendy Hartogensis, Stephan Dilchert, Ashley E. Mason, Benjamin L. Smarr   +4 more
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A Comprehensive Survey of Data Mining Techniques on Time Series Data for Rainfall Prediction

Journal of ICT Research and Applications, 2017
Time series data available in huge amounts can be used in decision-making. Such time series data can be converted into information to be used for forecasting.
Neelam Mishra, Hemant Kumar Soni, Sanjiv Sharma, A.K. Upadhyay   +3 more
doaj   +1 more source

Neural Network Ensembles for Time Series Prediction

, 2007
Rapidly evolving businesses generate massive amounts of time-stamped data sequences and defy a demand for massively multivariate time series analysis. For such data the predictive engine shifts from the historical auto-regression to modelling complex
Ruta, Dymitr, Gabrys, Bogdan, Dymitr Ruta, Bogdan Gabrys   +3 more
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T-Time: Threshold-Based Data Mining on Time Series [PDF]

2008 IEEE 24th International Conference on Data Engineering, 2008
Mining time series data is an important approach for the analysis in many application areas as diverse as biology, environmental research, medicine, or stock chart analysis. As nearly all data mining tasks on this kind of data depend on a distance function between two time series, a huge number of such functions has been developed during the last ...
Johannes Aßfalg, Hans-Peter Kriegel, Peer Kröger, Peter Kunath, Alexey Pryakhin, Matthias Renz   +5 more
openaire   +1 more source

Learning from medical data streams: an introduction [PDF]

, 2011
Clinical practice and research are facing a new challenge created by the rapid growth of health information science and technology, and the complexity and volume of biomedical data.
Rodrigues, P., Gaber, M.M., Gaber, M., Pechenizkiy, M., Pereira Rodrigues, P., Gama, J., Pechenizkiy, M.; id_orcid   +6 more
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Similarity Measures and Dimensionality Reduction Techniques for Time Series Data Mining

, 2012
The chapter is organized as follows. Section 2 will introduce the similarity matching problem on time series. We will note the importance of the use of efficient data structures to perform search, and the choice of an adequate distance measure. Section
Cannata, A., Alfredo Pulvirenti, Aliotta, M., Andrea Cannata, Cassisi, C., Carmelo Cassisi, Marco Aliotta, Placido Montalto, Montalto, P., Pulvirenti, A.   +9 more
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