Price prediction system – a predictive data analytics using arima model (Record no. 22740)

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003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250429093701.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250429b xxu||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency AIKTC-KRRC
Transcribing agency AIKTC-KRRC
100 ## - MAIN ENTRY--PERSONAL NAME
9 (RLIN) 25987
Author Vikranth, K.
245 ## - TITLE STATEMENT
Title Price prediction system – a predictive data analytics using arima model
250 ## - EDITION STATEMENT
Volume, Issue number Vol.14(3), Jan
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Chennai
Name of publisher, distributor, etc. ICT Academy
Year 2024
300 ## - PHYSICAL DESCRIPTION
Pagination 3304-3310p.
520 ## - SUMMARY, ETC.
Summary, etc. In India, agriculture represents the primary occupation of more than<br/>60% of the population. In terms of GDP, economic growth, traditional<br/>aspects, and social aspects, agriculture is essential for the country's<br/>development. The Indian farmers experienced numerous issues that<br/>have an impact on their way of life because the expansion in the<br/>agronomy business has not been as expected during the past two<br/>decades. Price fluctuation is one of the major issues faced by farmers,<br/>and as a result, they cannot get a reasonable price for their commodity.<br/>Also, it is very problematic to decide today without knowing the future<br/>price. So, this paper focused on finding a solution to the uncertainty<br/>problem in price faced by farmers that helps them take appropriate<br/>decisions during the farming process. The paper mainly concerns<br/>predictive data analytics using the ARIMA model, which predicts the<br/>price of areca nut products for the next 4 years using the past ten-year<br/>price dataset. The ARIMA model is a time series approach and a very<br/>appropriate framework for predicting future prices compared to other<br/>models. This paper includes a step-by-step procedure for the ARIMA<br/>techniques for forecasting price of agriculture commodity, and the<br/>outcomes are represented in the form of tables and graphical<br/>representations.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
9 (RLIN) 4622
Topical term or geographic name entry element Computer Engineering
700 ## - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 26024
Co-Author Nethravathi, P. S.
773 0# - HOST ITEM ENTRY
Title ICTACT Journal on Soft Computing (IJSC)
Place, publisher, and date of publication Chennai ICT Academy
856 ## - ELECTRONIC LOCATION AND ACCESS
URL https://ictactjournals.in/paper/IJSC_Vol_14_Iss_3_Paper_10_3304_3310.pdf
Link text Click here
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Articles Abstract Database
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    Dewey Decimal Classification     School of Engineering & Technology School of Engineering & Technology Archieval Section 29/04/2025   2025-0719 29/04/2025 29/04/2025 Articles Abstract Database
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