Developing a hybrid model for comparative analysis of financial data clustering algorithms
Purpose: Clustering algorithms are useful tools for understanding data structure and classifying them into different data sets. Due to the importance of using these algorithms in analyzing financial market data that have a high volume and scope, this study in order to select the best clustering algo...
Saved in:
Main Authors: | Mojtaba Movahedi, Mahdi Homayounfar, Mehdi Fadaei, Mansour Soufi |
---|---|
Format: | Article |
Language: | fas |
Published: |
Ayandegan Institute of Higher Education, Tonekabon,
2023-09-01
|
Series: | تصمیم گیری و تحقیق در عملیات |
Subjects: | |
Online Access: | https://www.journal-dmor.ir/article_145108_1c40bf9c90cdae35d219eaa1c7ede3d7.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Selection of green supplier by multi-moora combination method and two-stage clustering
by: Mahsa Niavand, et al.
Published: (2024-08-01) -
Financial performance evaluation of firms in BIST 100 index with ITARA and COBRA methods
by: Ali Katrancı, et al.
Published: (2025-01-01) -
Soft cluster-rectangle method for eliciting criteria weights in multi-criteria decision-making
by: Shervin Zakeri, et al.
Published: (2025-01-01) -
A new multi-attribute decision-making method for interval data using support vector machine
by: Ghassem Farajpour Khanaposhtani
Published: (2023-12-01) -
Novel Multiple Criteria Group Decision-Making Method Based on Hesitant Fuzzy Clustering Algorithm
by: Hongya Bian, et al.
Published: (2025-01-01)