MARKET CLUSTERING WITH THE ANT COLONY OPTIMIZATION ALGORITHM: A COMPARATIVE APPROACH WITH K-MEANS)

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

ZARE AHMADABADI HABIB; RAFIEI OMAM MAHBOOBEH; NASER SADRABADI ALIREZA

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF BUSINESS ADMINISTRATION RESEARCH Year:2017 | Volume:8 | Issue:16 Page(s): 17-36

Download Full-Text

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

View:

1,582

Download:

Cites:

Information Journal Paper

Title

MARKET CLUSTERING WITH THE ANT COLONY OPTIMIZATION ALGORITHM: A COMPARATIVE APPROACH WITH K-MEANS)

Author(s)

ZARE AHMADABADI HABIB | RAFIEI OMAM MAHBOOBEH | NASER SADRABADI ALIREZA | Issue Writer Certificate

Keywords

MARKET SEGMENTATIONQ1

CLUSTERINGQ1

META HEURISTIC ALGORITHMQ1

ANT COLONY OPTIMIZATION (ACO)Q1

Abstract

Nowadays, the ability of organizations has increased to identify target markets with data mining techniques. CLUSTERING is a method in which a cluster of objects is made somehow similar to characteristics. In a MARKET SEGMENTATION process, customers are segmented such that the customers of the same type are placed in the same group, and various groups have minimal affinity. Then, a marketing strategy should be matched to the specifications of these groups. With larger databases, researchers attempt to focus on finding effective CLUSTERING methods in order to make effective decisions. In this paper, we cluster the trail markets in Iran with the ant colony optimization algorithm, and, to further investigate the accuracy of this model, we compared the results with a classic CLUSTERING K-Mean. The paper presents an ant colony optimization methodology for optimal CLUSTERING of N objects into K clusters. The results show the higher accuracy of the ant colony optimization.

Cites

No record.

References

No record.

Cite

APA: Copy

ZARE AHMADABADI, HABIB, RAFIEI OMAM, MAHBOOBEH, & NASER SADRABADI, ALIREZA. (2017). MARKET CLUSTERING WITH THE ANT COLONY OPTIMIZATION ALGORITHM: A COMPARATIVE APPROACH WITH K-MEANS). JOURNAL OF BUSINESS ADMINISTRATION RESEARCH, 8(16 ), 17-36. SID. https://sid.ir/paper/197138/en

Vancouver: Copy

ZARE AHMADABADI HABIB, RAFIEI OMAM MAHBOOBEH, NASER SADRABADI ALIREZA. MARKET CLUSTERING WITH THE ANT COLONY OPTIMIZATION ALGORITHM: A COMPARATIVE APPROACH WITH K-MEANS). JOURNAL OF BUSINESS ADMINISTRATION RESEARCH[Internet]. 2017;8(16 ):17-36. Available from: https://sid.ir/paper/197138/en

IEEE: Copy

HABIB ZARE AHMADABADI, MAHBOOBEH RAFIEI OMAM, and ALIREZA NASER SADRABADI, “MARKET CLUSTERING WITH THE ANT COLONY OPTIMIZATION ALGORITHM: A COMPARATIVE APPROACH WITH K-MEANS),” JOURNAL OF BUSINESS ADMINISTRATION RESEARCH, vol. 8, no. 16 , pp. 17–36, 2017, [Online]. Available: https://sid.ir/paper/197138/en

Related Journal Papers