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A data mining framework for time series estimation
2010
Journal of Biomedical Informatics
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The performance of the proposed method was superior to that of a simple training-free approach of finding the optimal TTS-RTS pair by a conventional similarity-based search on RTS features. ...
In this work, we define target time series (TTS) and its related time series (RTS) as the output and input of a time series estimation process, respectively. ...
Acknowledgment The present work is supported in part by NINDS grants R21-NS055998, R21-NS055045, R21-NS059797 and R01-NS054881. ...
doi:10.1016/j.jbi.2009.11.002
pmid:19900575
pmcid:PMC2839011
fatcat:c7c7xvbhvzfn5fpfzljhade6gm
Adaptive query processing for time-series data
1999
Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '99
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As a result, these approaches are well suited for searching patterns, such as the similarity-based queries (e.g., example query Ql). Time-series Query Processing, Data Mining, Pattern Matching. ...
Keywords Many traditional approaches in time-series query processing are based on transforming data from the time domain into the frequency domain to optimize the indexes so that more efficient search ...
We present the IMPACTS system that maps atomic movements in a time series into a finite set of symbols to transform time series into symbol strings. ...
doi:10.1145/312129.318357
dblp:conf/kdd/HuangY99
fatcat:6lwlds4mqff77boysh4cvbzcjm
Linguistic Approach to Time Series Forecasting
[article]
2022
arXiv
pre-print
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They allow, with a high level of automation, to carry out short-term and medium-term forecasts of time series, characterized by trends and cyclicality, in particular, series of publication dynamics in ...
Further research may focus on the study of various criteria for the similarity of time series fragments, the use of nonlinear similarity criteria, the search for ways to automatically determine the rational ...
Also with a high level of automation they allow to make predictions of time series, which are characterized by cyclicality, in particular, the series of dynamics of publications in content monitoring systems ...
arXiv:2207.00985v1
fatcat:ckaw3f3jnjbevoioxglzgslmu4
Nonlinear system identification and fault detection using hierarchical clustering analysis and local linear models
2007
2007 Mediterranean Conference on Control & Automation
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The performance of the proposed nonlinear system identification is evaluated on two numerical examples: (i) time series prediction; (ii) identification of SISO system. ...
dynamics well in each region. ...
Before we proceed to design an unsupervised learning for searching of local dynamic regimes, nonlinear AR models for time series prediction and SISO system identification are briefly described. ...
doi:10.1109/med.2007.4433938
fatcat:tfeo76tiq5glrdj5begecyspcu
Evolutionary Optimization of Case-Based Forecasting Algorithms in Chaotic Environments
2021
Symmetry
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In this regard, a dynamic adaptation of precedent analysis algorithms based on the method of evolutionary modeling is proposed. ...
The problem of dynamic adaptation of prediction algorithms in chaotic environments based on identification of the situations-analogs in the database of retrospective observations is considered. ...
Acknowledgments: The authors acknowledge support by the Open Access Publication Funds of the TU Dresden.
Conflicts of Interest: The authors declare no conflict of interest. Symmetry 2021, 13, 301 ...
doi:10.3390/sym13020301
fatcat:7jbcfhe7enbg5nxzlbfoj24iye
A dynamic predictor selection method based on recent temporal windows for time series forecasting
2021
IEEE Access
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The development of accurate forecasting systems for real-world time series modeling is a challenging task. ...
This paper proposes a dynamic selection approach entitled Dynamic Selection based on the Nearest Windows (DSNAW) that selects one or more competent models according to their performance in the region of ...
The development of accurate forecasting systems has been a central goal in the time series modeling area. ...
doi:10.1109/access.2021.3101741
fatcat:pzrebsohd5awrjrkc7yvtyk23i
Mining and Forecasting of Big Time-series Data
2015
Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data - SIGMOD '15
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We review the state of the art in four related fields: (1) similarity search and pattern discovery, (2) linear modeling and summarization, (3) non-linear modeling and forecasting, and (4) the extension ...
of time-series mining and tensor analysis. ...
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation, ARL, or other ...
doi:10.1145/2723372.2731081
dblp:conf/sigmod/SakuraiMF15
fatcat:dsmv2sqs35bm5ifeqr4qnuz6ty
Principles for Development of Predictive Stability Models of Social and Economic Systems on the basis of DTW
2020
E3S Web of Conferences
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The rationale for the selection of metrics on the basis of a dynamic time-warping algorithm which allows to carry out clustering of the system attribute space. ...
This paper presents the concept for the development of predictive models of social and economic system evolution providing the necessity of combining solution search optimization algorithms and methods ...
Acknowledgements The study was conducted under the sponsorship of the grant of the Russian Foundation for Basic Research No. 18.07.00170. ...
doi:10.1051/e3sconf/202020808001
fatcat:lht6ku7f4fa6rnjd2p3yk5rpki
Automated parameter specification in dynamic feedback models based on behavior pattern features
2011
System Dynamics Review
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The pattern identifi cation algorithm used enables a parameter search process based on qualitative features of a desired behavior pattern, even in the absence of a reference data series. ...
However, due to the non-linear nature of these models it is generally hard to foresee changes in the dynamic behavior as a consequence of even marginal parameter changes. ...
However, the emphasis is on the dynamic behavior of the system in most SD studies (and in many simulation-based studies). ...
doi:10.1002/sdr.457
fatcat:gpgvpne7t5fvxc36ka3zcxssmq
Temporal web dynamics and its application to information retrieval
2013
Proceedings of the sixth ACM international conference on Web search and data mining - WSDM '13
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Web Select regions of interest (x-y location, dom structure, text) E.g., stock price, traffic status, headlines about wsdm, ... Operators for manipulating streams of interest Filter Link Visualize ...
Traditional IR: single snap shot Word/query trends: aggregates over docs Document change: aggregates over terms (Word,Document) trends: Zoetrope System that enables interaction with historical ...
Weak discriminators is easily described by a simple linear time series model, 2. ...
doi:10.1145/2433396.2433500
dblp:conf/wsdm/RadinskyDDSDC13
fatcat:v3r5yqpnwjcezm35ux4v5eiyse
An inductive approach to ecological time series modelling by evolutionary computation
2001
Ecological Modelling
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Building time series models for ecological systems that can be physically interpreted is important both for understanding the dynamics of these natural systems and the development of decision support systems ...
This work describes the application of an evolutionary computation framework for the discovery of predictive equations and rules for phytoplankton abundance in freshwater lakes from time series data. ...
Institute of Environmental Studies in Tsukuba, Japan, for providing data of the Lake Kasumigaura. ...
doi:10.1016/s0304-3800(01)00313-1
fatcat:m7pmag3glzggtfv2f34dez2f2a
DTW-Based Subsequence Similarity Search on AMD Heterogeneous Computing Platform
2013
2013 IEEE 10th International Conference on High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing
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Subsequence similarity search is one of the most common subroutines in time series data mining algorithms. ...
In this paper, we propose a full system implementation for subsequence similarity search on AMD heterogeneous computing platform, including complete normalization pre-processing, two kinds of improved ...
As is mentioned in section I, because of the unsatisfactory conditions in reality, Euclidean distance was not so good to deal with time series similarity search, so Dynamic Time Warping distance was proposed ...
doi:10.1109/hpcc.and.euc.2013.149
dblp:conf/hpcc/HuangDSWWY13
fatcat:i4c6cfbmvzhbtp47sp5ispxrnu
Model-based search in large time series databases
2011
Proceedings of the 4th International Conference on PErvasive Technologies Related to Assistive Environments - PETRA '11
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We also perform a comparative evaluation of exemplar-based search using dynamic time warping (DTW), and model-based search using Hidden Markov Models (HMMs), on large real datasets. ...
In our experiments, when the number of training objects per model is sufficiently high, model-based search using HMMs produces more accurate search results than exemplarbased search using DTW. ...
Panagiotis Papapetrou and Jaakko Hollmén were supported in part by the Algorithmic Centre of Excellence (ALGODAN). ...
doi:10.1145/2141622.2141666
dblp:conf/petra/KotsifakosAPHG11
fatcat:br7yeelpsrfkzpztotkntjndf4
A data-driven framework for remaining useful life estimation
2017
Vietnam Journal of Science and Technology
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The methods involve the use of some other data processing techniques including wavelets denoise and similarity search. ...
The approaches are suitable for problems in which a data library of complete runs of a system is available. Given a non-complete run of the system, the RUL can be predicted using these approaches. ...
Similarity search Similarity search has attracted a lot of research attention recently. A brief description of the technique of "similarity search" in time series data was done by Goldin et al. ...
doi:10.15625/2525-2518/55/5/8582
fatcat:y66g7dhnuva67a3a2vg7juyebm
CompEngine: a self-organizing, living library of time-series data
[article]
2019
arXiv
pre-print
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Using a canonical feature-based representation, CompEngine places all time series in a common space, regardless of their origin, allowing users to upload their data and immediately explore interdisciplinary ...
Modern biomedical applications often involve time-series data, from high-throughput phenotyping of model organisms, through to individual disease diagnosis and treatment using biomedical data streams. ...
Acknowledgements We thank Rachael Fulcher for designing the infographic in Fig. 2 . ...
arXiv:1905.01042v1
fatcat:4bcnjsbgqvbkdcl4cec4pghjoy
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