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Software Design Challenges in Time Series Prediction Systems Using Parallel Implementation of Artificial Neural Networks
Joint Authors
Manikandan, Narayanan
Subha, Srinivasan
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-01-03
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Software development life cycle has been characterized by destructive disconnects between activities like planning, analysis, design, and programming.
Particularly software developed with prediction based results is always a big challenge for designers.
Time series data forecasting like currency exchange, stock prices, and weather report are some of the areas where an extensive research is going on for the last three decades.
In the initial days, the problems with financial analysis and prediction were solved by statistical models and methods.
For the last two decades, a large number of Artificial Neural Networks based learning models have been proposed to solve the problems of financial data and get accurate results in prediction of the future trends and prices.
This paper addressed some architectural design related issues for performance improvement through vectorising the strengths of multivariate econometric time series models and Artificial Neural Networks.
It provides an adaptive approach for predicting exchange rates and it can be called hybrid methodology for predicting exchange rates.
This framework is tested for finding the accuracy and performance of parallel algorithms used.
American Psychological Association (APA)
Manikandan, Narayanan& Subha, Srinivasan. 2016. Software Design Challenges in Time Series Prediction Systems Using Parallel Implementation of Artificial Neural Networks. The Scientific World Journal،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1120543
Modern Language Association (MLA)
Manikandan, Narayanan& Subha, Srinivasan. Software Design Challenges in Time Series Prediction Systems Using Parallel Implementation of Artificial Neural Networks. The Scientific World Journal No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1120543
American Medical Association (AMA)
Manikandan, Narayanan& Subha, Srinivasan. Software Design Challenges in Time Series Prediction Systems Using Parallel Implementation of Artificial Neural Networks. The Scientific World Journal. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1120543
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1120543