UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 10 Issue 11
November-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2311127


Registration ID:
525764

Page Number

b214-b218

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Title

TS Predictor - An Approach to Analyze and Forecast Time Series Data

Authors

Abstract

In this work, a methodology has been proposed for the analysis & forecasting of time series data. The methodology involves collecting historical stock data, preprocessing the data such as handling of incomplete data, duplicate data, and incorrectly formatted data, dealing with outliers, data normalization to ensure all inputs are on a similar scale, splitting the dataset into training and testing data sets, organize the dataset into sequential pattern. Train the proposed model using training dataset. Finally we have used the test dataset to evaluate the performance of the model. Our proposed model produces better accuracy in prediction when compared to the similar work done in the same field.

Key Words

Time series data analysis, data forecasting, training dataset, testing dataset, noise removal, data normalization, sequential pattern, Long short-term memory.

Cite This Article

"TS Predictor - An Approach to Analyze and Forecast Time Series Data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 11, page no.b214-b218, November-2023, Available :http://www.jetir.org/papers/JETIR2311127.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"TS Predictor - An Approach to Analyze and Forecast Time Series Data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 11, page no. ppb214-b218, November-2023, Available at : http://www.jetir.org/papers/JETIR2311127.pdf

Publication Details

Published Paper ID: JETIR2311127
Registration ID: 525764
Published In: Volume 10 | Issue 11 | Year November-2023
DOI (Digital Object Identifier):
Page No: b214-b218
Country: Barrackpore, Kolkata, West Bengal, India .
Area: Science & Technology
ISSN Number: 2349-5162
Publisher: IJ Publication


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