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ANALISA PENGELOMPOKAN PENUNGGAKAN PEMBAYARAN LISTRIKRN(STUDI KASUS PT. PLN (PERSERO),CABANG RNMERDUATI BANDA ACEH) [PDF]

, 2015
Analisa pengelompokan data pelanggan PT. PLN (persero) Merduati Banda Aceh berdasarkan data pelanggan bertujuan untuk mengelompokan data pelanggan yang menunggak dan tidak menunggak dan membandingkan hasil analisa berdasarkan nilai validitas menggunakan ...
Khusnul Azima
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On the selection of m for Fuzzy c-Means [PDF]

Advances in Intelligent Systems Research, 2015
Fuzzy c-means is a well known fuzzy clustering algorithm. It is an unsupervised clustering algorithm that permits us to build a fuzzy partition from data. The algorithm depends on a parameter m which corresponds to the degree of fuzziness of the solution. Large values of m will blur the classes and all elements tend to belong to all clusters.
openaire   +1 more source

Development of a Prediction Model for Progression Risk in High‐Grade Gliomas Based on Habitat Radiomics and Pathomics

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high‐grade gliomas. Methods This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high‐grade gliomas (52 ...
Yuchen Zhu, Yuxi Gong, Weilin Xu, Xingjian Sun, Gefei Jiang, Lei Qiu, Kexin Shi, Mengxing Wu, Yinjiao Fei, Jinling Yuan, Jinyan Luo, Yurong Li, Yuandong Cao, Minhong Pan, Shu Zhou   +14 more
wiley   +1 more source

Combining Fuzzy C-Means Clustering with Fuzzy Rough Feature Selection

Applied Sciences, 2019
With the rapid development of the network, data fusion becomes an important research hotspot. Large amounts of data need to be preprocessed in data fusion; in practice, the features of datasets can be filtered to reduce the amount of data.
Ruonan Zhao, Lize Gu, Xiaoning Zhu
doaj   +1 more source

Implementasi Algoritma Fuzzy C - Means Clustering Dan Simple Additive Weighting Dalam Pemberian Bantuan Program Peningkatan Kualitas Kawasan Permukiman [PDF]

, 2016
Permasalahan kemiskinan di Indonesia sudah sangat mendesak untuk ditangani, khususnya pada wilayah perkotaan. Kementrian PUPR menyatakan salah satu kondisi fisik masyarakat miskin adalah tidak memiliki akses sarana dan prasarana dasar lingkungan yang ...
Andreswari, D. (Desi), Ernawati, E. (Ernawati), Shugara, R. (Robbie)   +2 more
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Remote Assessment of Ataxia Severity in SCA3 Across Multiple Centers and Time Points

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Spinocerebellar ataxia type 3 (SCA3) is a genetically defined ataxia. The Scale for Assessment and Rating of Ataxia (SARA) is a clinician‐reported outcome that measures ataxia severity at a single time point. In its standard application, SARA fails to capture short‐term fluctuations, limiting its sensitivity in trials.
Marcus Grobe‐Einsler, Vivian Maas, Arian Taheri Amin, Jennifer Faber, Tamara Schaprian, Katharina Hill, Matthis Synofzik, Lisa H. Graf, Heike Jacobi, Manuela Lima, Ana F. Ferreira, Bart P. van de Warrenburg, Ilse H. J. Willemse, Dagmar Timmann, Andreas Thieme, Paola Giunti, Hector Garcia‐Moreno, Magda M. Santana, Jeannette Hübener‐Schmid, Elin H. Davies, Thomas Klockgether   +20 more
wiley   +1 more source

Bilateral Weighted Fuzzy C-Means Clustering

Iranian Journal of Electrical and Electronic Engineering, 2012
Nowadays, the Fuzzy C-Means method has become one of the most popular clustering methods based on minimization of a criterion function. However, the performance of this clustering algorithm may be significantly degraded in the presence of noise.
A. H. Hadjahmadi, M. M. Homayounpour, M. Ahadi   +2 more
doaj  

Priority Road Restoration Classification Using Fuzzy C-Means: A Case Study In Samarinda City

Jurnal Teknologi dan Sistem Komputer, 2017
One of the factors traffic accidents is caused by a damaged road. Therefore, road improvements based on the priorities scale is indispensable. This study implements the Fuzzy C-means method.
Novianti Puspitasari, Rosmasari Rosmasari, Stefanie Stefanie   +2 more
doaj   +1 more source

FP-Conv-CM: Fuzzy Probabilistic Convolution C-Means

Mathematics, 2023
Soft computing models based on fuzzy or probabilistic approaches provide decision system makers with the necessary capabilities to deal with imprecise and incomplete information.
Karim El Moutaouakil, Vasile Palade, Safaa Safouan, Anas Charroud   +3 more
doaj   +1 more source

Fuzzy Image Segmentation using Suppressed Fuzzy C-Means Clustering (SFCM) [PDF]

, 2004
Clustering algorithms are highly dependent on the features used and the type of the objects in a particular image. By considering object similar surface variations (SSV) as well as the arbitrariness of the fuzzy c-means (FCM) algorithm for pixel location,
Ali, Ameer, Karmakar, Gour C., Dooley, Laurence S.   +2 more
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