Title
FCM Algorithm: Analysis of the Membership Function Influence and Its consequences for fuzzy clustering
Date Issued
07 August 2020
Access level
metadata only access
Resource Type
conference paper
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
Image segmentation in satellite images is a task widely investigated since we can extract some information of an image and analyze it. We propose to use a weighted factor for each of the distances used to calculate the degree of membership of each element to the cluster. In this way, we seek to reduce the influence of the upper and the lower bounds on the FCM equa. tion. This paper reports preliminary results of the experiments and shows that the proposed algorithm performs accurately on a real dataset. For the evaluation of the algorithm, different cluster validity indexes are employed.
Language
English
OCDE Knowledge area
Otras ingenierías y tecnologías
Ciencias de la computación
Subjects
Scopus EID
2-s2.0-85097548833
Resource of which it is part
2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings
ISBN of the container
9781728194066
Conference
2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings
Sources of information:
Directorio de Producción Científica
Scopus