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Identification of Concurrent Control Chart Patterns in Time Series
English
2015
International Journal of Innovative Research in Science, Engineering and Technology
English
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It will identify independent components hidden in mixture patterns and input those independent components to decision trees for recognition of as many as eight separate control chart patterns. ...
From our experimental results, it can be concluded that proposed scheme may efficiently analyzemixture patterns in time-series of medical, financial and any other applications. ...
An ICA has been successfully applied in various fields of multivariate data procession from image processing, face recognition to time series prediction [14] . ...
doi:10.15680/ijirset.2015.0406167
fatcat:6vjnft46x5h3lg3h2wj3hio7pq
Identifying Temporal Patterns for Characterization and Prediction of Financial Time Series Events
[chapter]
2001
Lecture Notes in Computer Science
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The TSDM framework and concepts are reviewed, and the applicable TSDM method is discussed. Finally, the TSDM method is applied to time series generated by a basket of financial securities. ...
The novel Time Series Data Mining (TSDM) framework is applied to analyzing financial time series. The TSDM framework adapts and innovates data mining concepts to analyzing time series data. ...
Review of Time Series Analysis Techniques The analysis of financial time series has a long history. ...
doi:10.1007/3-540-45244-3_5
fatcat:fzc3dzlzpje65dmghvrnacjoza
Recent Techniques of Clustering of Time Series Data: A Survey
2012
International Journal of Computer Applications
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Time-Series clustering is one of the important concepts of data mining that is used to gain insight into the mechanism that generate the time-series and predicting the future values of the given time-series ...
In this paper, we have shown the survey and summarization of previous work that investigated the clustering of time series in various application domains ranging from science, engineering, business, finance ...
component
analysis
Euclidean
Modified k-means
Real world stock time-
series
Jian Xin Wu
Independent component
analysis
N/A
support vector
regression
Financial time-series
Geert Verdoolaege ...
doi:10.5120/8282-1278
fatcat:v5d6vcatmrdnvjj55tubb736m4
Application of improved convolution neural network in financial forecasting
2022
Journal of Organizational and End User Computing
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Firstly, the noise of the collected data set is deleted, and then the clustering result is more stable by principal component analysis. ...
In order to deduce the source of monetary funds and determine their whereabouts, financial information and prediction have become a scientific method that can not be ignored in the development of national ...
pattern in time series data, which is related to the nature of financial information and can be understood in time. ...
doi:10.4018/joeuc.289222
fatcat:orvbofmj55hv5i33ssg3cymfgq
Real Time Iris Image Segmentation for Non Co-Operative Environment
2014
International Journal of Computer Applications
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as Independent Component Analysis (ICA). ...
To find a linear representation of non gaussian data, Independent Component Analysis is used & because of this the components are statistically independent, or as independent as possible. ...
doi:10.5120/15273-3944
fatcat:iovtnxlnijcfrbwnk4uod2junu
Pattern Classification of Signals Using Fisher Kernels
2012
Mathematical Problems in Engineering
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The intention of this study is to gauge the performance of Fisher kernels for dimension simplification and classification of time-series signals. ...
For assessing the fate of each company, we have collected financial time-series composed of weekly closing stock prices in a common time frame, using Thomson Datastream software. ...
Acknowledgments The authors extend their sincere thanks to NSERC Granting Council, CFI/OIT, and Canada Research Chairs program for funding the research. ...
doi:10.1155/2012/467175
fatcat:faxkpf3gmfc3xlbomhkqy2prci
Irregularity, volatility, risk, and financial market time series
2004
Proceedings of the National Academy of Sciences of the United States of America
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instability ͉ random walk S eries of sequential data are pivotal to much of financial analysis. ...
The purpose of this article is to demonstrate several applications of ApEn to the evaluation of financial data. ...
To better understand the utility of ApEn as applied herein, we consider the extant approaches to financial time series analysis. ...
doi:10.1073/pnas.0405168101
pmid:15358860
pmcid:PMC518821
fatcat:chd2i6miy5fp3pw54z36vd5kvy
Neural Networks and Empirical Research in Accounting
1996
Accounting and Business Research
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This article seeks to provide an overview of the potential role of neural network (connectionist) meth<>dalogy in empirical accounting research. ...
A non-technical overview of neural network methodology is givelL along with guidelines to help accounting researchers interested in applying these new tools to recognise the potential dangers and strengths ...
Drawing on the substantial literature applying connectionist approaches of a pattern recognition nature in financial forecasting, such as real-time market trading and technical analysis (eg., Baestaens ...
doi:10.1080/00014788.1996.9729524
fatcat:t3nezgyqabbjzkajxy275c6upe
Pattern recognition using hidden Markov models in financial time series
2017
Acta et Commentationes Universitatis Tartuensis de Mathematica
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The classication algorithm correctly recognizes 93% of the provided patterns. Thanks to the analysis of the false positive examples, we nally designed some more lters to reduce them. ...
Our aim consists in developing a software which can recognize M trading patterns in real time using Hidden Markov Models (HMMs). ...
The authors wish to thank the referees for the remarks which helped to improve the version of the paper. ...
doi:10.12697/acutm.2017.21.02
fatcat:jgsl5zrxl5czln5ulqxaahj3pi
The application of dynamic self-organised multilayer network inspired by the Immune Algorithm for weather signals forecast
2015
2015 Third International Conference on Technological Advances in Electrical, Electronics and Computer Engineering (TAEECE)
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, medical diagnostics and pattern recognition for big data. ...
This can extend the application of the proposed network to scientifically analyse different types of big data. ...
ANNs have been proposed as useful tools in time series analysis in a variety of applications. ...
doi:10.1109/taeece.2015.7113607
fatcat:asar63xgmjhejd2dtj7hn7oc5u
The Use of Artificial Intelligence in Building Automated Trading Systems
2014
Journal of clean energy technologies
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It summarizes the findings of systemic approaches over building trade system and an application of the AI (mainly genetic algorithms and neural networks) to find the best solutions, while the use of artificial ...
The article introduces the reader with the concept of long term success in trading in financial markets. ...
Leading analysts have tried to disaggregate the market behavior by time series models. Decomposition of time series (see above) is the simplest approach to the modeling of time series [7] , [12] . ...
doi:10.7763/ijcte.2014.v6.883
fatcat:dud4glbtdzfubntzz7s5dpnmt4
Speech Recognition in ATMs: Application of Linear Predictive Coding and Support Vector Machines
2017
International Journal for Research in Applied Science and Engineering Technology
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This hybrid architecture of LPC and SVM produced rather good recognition accuracy of 80.25%. ...
Today, Automated Teller Machines (ATMs) are extensively used by people for financial transactions. It provides a convenient, fast and easy way for customers to access cash. ...
CONCLUSIONS The research in the domain of audio and speech recognition is still going on and this work is an application of speech recognition for financial transactions in ATMs. ...
doi:10.22214/ijraset.2017.3100
fatcat:h6lkb5f2ofeilikv647rcgs5lu
Gabor filter for enhanced recognition of assisted turning events
2011
2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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In the RCT, it is necessary to objectively confirm the reported times of assisted turning by certified nurse assistants using activity data. ...
Activity peaks in Gaussian-smoothed activity data were unable to confirm all turning events in a supporting pilot study with observer notes of assisted turns. ...
Acknowledgments This work was supported by the National Institutes of Health under grant R01 NR009680. ...
doi:10.1109/iembs.2011.6091941
pmid:22256165
pmcid:PMC3601032
dblp:conf/embc/PadhyeZRB11
fatcat:spwp5yd6yvajlpbd47daosw56i
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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of time-series mining and tensor analysis. ...
Time-series data analysis is becoming of increasingly high importance, thanks to the decreasing cost of hardware and the increasing on-line processing capability. ...
Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on. ...
doi:10.1145/2723372.2731081
dblp:conf/sigmod/SakuraiMF15
fatcat:dsmv2sqs35bm5ifeqr4qnuz6ty
Adaptive nonstationary regression analysis
2008
Pattern Recognition (ICPR), Proceedings of the International Conference on
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from the full stationarity of instant models to their absolute independence in time. ...
The problem of finding the most appropriate subset of features or regressors is the generic challenge of Machine Learning problems like regression estimation or pattern recognition. ...
We consider the time series to be processed ( , 1,..., ) t y t N = (2) as the observable part of a two-component random process, whose hidden part is the unknown sequence of time-varying regression coef ...
doi:10.1109/icpr.2008.4761666
dblp:conf/icpr/KrasotkinaM08
fatcat:kac3pkzi75dg3da7sqqh76mcge
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