Comparison of k-means and fuzzy c-means algorithms on different cluster structures
Z Cebeci, F Yildiz - Journal of Agricultural Informatics, 2015 - journal.magisz.org
In this paper the K-means (KM) and the Fuzzy C-means (FCM) algorithms were compared
for their computing performance and clustering accuracy on different shaped cluster …
for their computing performance and clustering accuracy on different shaped cluster …
A survey on image segmentation methods using clustering techniques
Image segmentation has been considered as the first step in the image processing. An
efficient segmentation result would make it easier for further analysis of image processing …
efficient segmentation result would make it easier for further analysis of image processing …
Cluster analysis menggunakan algoritma Fuzzy C-means dan K-means untuk klasterisasi dan pemetaan lahan pertanian di Minahasa Tenggara
Penelitian ini bertujuan untuk melakukan analisis cluster dan implementasinya dengan
menggunakan algoritma fuzzy c-means (FCM) dan kmeans (KM) untuk mengelola data …
menggunakan algoritma fuzzy c-means (FCM) dan kmeans (KM) untuk mengelola data …
[PDF][PDF] Kesimpulan dan saran
V Bab - BAB II, 2016 - e-journal.uajy.ac.id
BAB V KESIMPULAN DAN SARAN 5.1. Pendahuluan Bab ini terdapat kesimpulan dan saran
dari penulis. Kesimpulan yang diperoleh dari Page 1 BAB V KESIMPULAN DAN SARAN 5.1 …
dari penulis. Kesimpulan yang diperoleh dari Page 1 BAB V KESIMPULAN DAN SARAN 5.1 …
Fuzzy clustering algorithms with distance metric learning and entropy regularization
Clustering has been used in various fields, such as image processing, data mining, pattern
recognition, and statistical analysis. Generally, clustering algorithms consider all variables …
recognition, and statistical analysis. Generally, clustering algorithms consider all variables …
Crack detection in X-ray images using fuzzy index measure
CH Linda, GW Jiji - Applied Soft Computing, 2011 - Elsevier
Crack of the bone is a very serious medical condition. In medical applications, sensitivity in
detecting medical problems and accuracy of detection are often in conflict. Computer …
detecting medical problems and accuracy of detection are often in conflict. Computer …
Unsupervised algorithms for microarray sample stratification
The amount of data made available by microarrays gives researchers the opportunity to
delve into the complexity of biological systems. However, the noisy and extremely high …
delve into the complexity of biological systems. However, the noisy and extremely high …
[PDF][PDF] Develo** of the cyber security system based on clustering and formation of control deviation signs
The cyber security (CS) adaptive system is developed. It is based on advanced algorithms of
anomalies signs space partitioning and attacks on clusters. A new approach of solving the …
anomalies signs space partitioning and attacks on clusters. A new approach of solving the …
Perbandingan metode K-Means dengan fuzzy C-Means untuk analisa karakteristik mahasiswa berdasarkan kunjungan ke perpustakaan (Studi kasus Sekolah Tinggi …
NPE Merliana - 2015 - e-journal.uajy.ac.id
Kurangnya minat membaca pada mahasiswa khususnya menjadi perhatian bagi lembaga
pendidikan, karena membaca dapat menambah wawasan, pengetahuan dan informasi …
pendidikan, karena membaca dapat menambah wawasan, pengetahuan dan informasi …
A fuzzy approach to robust regression clustering
A new robust fuzzy regression clustering method is proposed. We estimate coefficients of a
linear regression model in each unknown cluster. Our method aims to achieve robustness …
linear regression model in each unknown cluster. Our method aims to achieve robustness …