NEW CLUSTERING TECHNIQUE USING ARTIFICIAL IMMUNE SYSTEM AND HIERARCHICAL TECHNIQUE

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.

JAFARIAN MOGHADDAM AHMAD REZA; BARZINPOUR FARNAZ; FATHIAN MOHAMMAD

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

Journal Paper

Paper Information

Journal: SIGNAL AND DATA PROCESSING Year:2017 | Volume:13 | Issue:4 (SERIAL 30) Page(s): 133-145

Download Full-Text

Persian Verion

View:

695

Download:

Cites:

Information Journal Paper

Title

NEW CLUSTERING TECHNIQUE USING ARTIFICIAL IMMUNE SYSTEM AND HIERARCHICAL TECHNIQUE

Author(s)

JAFARIAN MOGHADDAM AHMAD REZA | BARZINPOUR FARNAZ | FATHIAN MOHAMMAD | Issue Writer Certificate

Keywords

CLUSTERING ANALYSISQ2

ARTIFICIAL IMMUNE SYSTEM (AIS)Q2

HIERARCHICAL CLUSTERINGQ1

Abstract

Artificial immune system (AIS) is one of the most meta-heuristic algorithms to solve complex problems. With a large number of data, creating a rapid decision and stable results are the most challenging tasks due to the rapid variation in real world. Clustering technique is a possible solution for overcoming these problems. The goal of CLUSTERING ANALYSIS is to group similar objects. AIS algorithm can be used in data CLUSTERING ANALYSIS. Although AIS is able to good display configure of the search space, but determination of clusters of data set directly using the AIS output will be very difficult and costly. Accordingly, in this paper a two-step algorithm is proposed based on AIS algorithm and HIERARCHICAL CLUSTERING technique. High execution speed and no need to specify the number of clusters are the benefits of the HIERARCHICAL CLUSTERING technique. But this technique is sensitive to outlier data. So, in the first stage of introduced algorithm using the proposed AIS algorithm, search space was investigated and the configuration space and therefore outlier data are determined. Then in second phase, using HIERARCHICAL CLUSTERING technique, clusters and their number are determined. Consequently, the first stage of proposed algorithm eliminates the disadvantages of the HIERARCHICAL CLUSTERING technique, and AIS problems will be resolved in the second stage of the proposed algorithm. In this paper, the proposed algorithm is evaluated and assessed through two metrics that were identified as (i) execution time (ii) Sum of Squared Error (SSE): the average total distance between the center of a cluster with cluster members used to measure the goodness of a clustering structure. Finally, the proposed algorithm has been implemented on a real sample data composed of the earthquake in Iran and has been compared with the similar algorithm titled Improved Ant System-based Clustering algorithm (IASC). IASC is based on Ant Colony System (ACS) as the meta-heuristics clustering algorithm. It is a fast algorithm and is suitable for dynamic environments. Table 1 shows the results of evaluation. The results showed that the proposed algorithm is able to cover the drawbacks in AIS and HIERARCHICAL CLUSTERING techniques and the other hand has high precision and acceptable run speed.

Cites

No record.

References

No record.

Cite

APA: Copy

JAFARIAN MOGHADDAM, AHMAD REZA, BARZINPOUR, FARNAZ, & FATHIAN, MOHAMMAD. (2017). NEW CLUSTERING TECHNIQUE USING ARTIFICIAL IMMUNE SYSTEM AND HIERARCHICAL TECHNIQUE. SIGNAL AND DATA PROCESSING, 13(4 (SERIAL 30) ), 133-145. SID. https://sid.ir/paper/160788/en

Vancouver: Copy

JAFARIAN MOGHADDAM AHMAD REZA, BARZINPOUR FARNAZ, FATHIAN MOHAMMAD. NEW CLUSTERING TECHNIQUE USING ARTIFICIAL IMMUNE SYSTEM AND HIERARCHICAL TECHNIQUE. SIGNAL AND DATA PROCESSING[Internet]. 2017;13(4 (SERIAL 30) ):133-145. Available from: https://sid.ir/paper/160788/en

IEEE: Copy

AHMAD REZA JAFARIAN MOGHADDAM, FARNAZ BARZINPOUR, and MOHAMMAD FATHIAN, “NEW CLUSTERING TECHNIQUE USING ARTIFICIAL IMMUNE SYSTEM AND HIERARCHICAL TECHNIQUE,” SIGNAL AND DATA PROCESSING, vol. 13, no. 4 (SERIAL 30) , pp. 133–145, 2017, [Online]. Available: https://sid.ir/paper/160788/en

Related Journal Papers