Volume 12 (2024)
Volume 11 (2023)
Volume 10 (2022)
Volume 9 (2021)
Volume 8 (2020)
Volume 7 (2019)
Volume 6 (2018)
Volume 5 (2017)
Volume 4 (2016)
Volume 3 (2015)
Volume 2 (2014)
Volume 1 (2013)
F.4.18. Time series analysis
Time Series Clustering based on Aggregation and Selection of Extracted Features

Ali Ghorbanian; Hamideh Razavi

Volume 11, Issue 2 , April 2023, , Pages 303-314

https://doi.org/10.22044/jadm.2023.13089.2449

Abstract
  In time series clustering, features are typically extracted from the time series data and used for clustering instead of directly clustering the data. However, using the same set of features for all data sets may not be effective. To overcome this limitation, this study proposes a five-step algorithm ...  Read More

H.3. Artificial Intelligence
Forecasting Gold Price using Data Mining Techniques by Considering New Factors

A.R. Hatamlou; M. Deljavan

Volume 7, Issue 3 , July 2019, , Pages 411-420

https://doi.org/10.22044/jadm.2018.6114.1727

Abstract
  Gold price forecast is of great importance. Many models were presented by researchers to forecast gold price. It seems that although different models could forecast gold price under different conditions, the new factors affecting gold price forecast have a significant importance and effect on the increase ...  Read More

Timing analysis
Fuzzy clustering of time series data: A particle swarm optimization approach

Z. Izakian; M. Mesgari

Volume 3, Issue 1 , March 2015, , Pages 39-46

https://doi.org/10.5829/idosi.JAIDM.2015.03.01.05

Abstract
  With rapid development in information gathering technologies and access to large amounts of data, we always require methods for data analyzing and extracting useful information from large raw dataset and data mining is an important method for solving this problem. Clustering analysis as the most commonly ...  Read More