ARTIFICIAL BEE COLONY BASED FUZZY CLUSTERING ALGORITHMS FOR MRI IMAGE SEGMENTATION
Published In: INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTER SCIENCE AND ELECTRONICS ENGINEERING
Author(s): AYAT ALROSAN , NORITA NORWAWI , WALEED ALOMOUSH , WEDIAH ISMAIL
Abstract: Fuzzy clustering algorithms (FCM) have some disadvantage. The main disadvantage is the cluster centroids initialization sensitivity and trapped in local optima. This study proposed a novel clustering method by coupling artificial bee colony with fuzzy c-means (ABC-FCM) algorithm. The technique exploits the superior capabilities of ABC in searching for optimum initial cluster centers and uses these clusters as the input for FCM, thus improving the segmentation of MRI brain images. The performance of the newly developed approach was tested using two sets of MRI images: simulated brain data and real MRI images.
- Publication Date: 09-Mar-2014
- DOI: 10.15224/978-1-63248-000-2-75
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SEISMIC SAFETY ASSESSMENT OF EXISTING BURIED PIPELINES
Published In: INTERNATIONAL CONFERENCE ON ADVANCES IN CIVIL, STRUCTURAL, ENVIRONMENTAL AND BIO-TECHNOLOGY
Author(s): BENSAIBI MAHMOUD , DAVENNE LUC , HALFAYA FATMA ZOHRA
Abstract: Statistical analysis was conducted on the effect of different parameters of buried pipelines that play a significant role on their seismic damage. Based on the results thus obtained, a simple criteria was proposed for the preliminary evaluation of seismic safety (or vulnerability) of existing buried pipelines. The adequacy of the criteria was examined and the water supply network of Blida city was studied.
- Publication Date: 09-Mar-2014
- DOI: 10.15224/978-1-63248-001-9-01
- Views: 0
- Downloads: 0