Results 61 to 70 of about 376,662 (290)

A Novel Linguistic Relational Fuzzy C-Means

IEEE Access
In real-world applications, sometimes there are uncertainties in the data sets whether from the collection process or from the natural languages. Moreover, the data may come in the form of fuzzy relation.
Peerawich Phaknonkul, Sansanee Auephanwiriyakul, Nipon Theera-Umpon   +2 more
doaj   +1 more source

Penerapan Fuzzy C-Means dalam Sistem Pendukung Keputusan untuk Penentuan Penerima Bantuan Langsung Masyarakat (BLM) PNPM-MPd (Studi Kasus PNPM-MPd Kec. Ngadirojo Kab. Pacitan) [PDF]

, 2013
PNPM Mandiri Perdesaan adalah program untuk mempercepat penanggulangan kemiskinan secara terpadu dan berkelanjutan. Bentuk kegiatan dari PNPM-MPd adalah memberikan bantuan langsung kepada masyarakat.
Ahmadi, A. (Aziz), Hartati, S. (Sri)
core  

A Fuzzy C-Means Algorithm for Fingerprint Segmentation [PDF]

, 2015
Fingerprint segmentation is a crucial step of an automatic fingerprint identification system, since an accurate segmentation promote both the elimination of spurious minutiae close to the foreground boundaries and the reduction of the computation time of the following steps.
Pedro M. Ferreira 0002, Ana Filipa Sequeira, Ana Rebelo   +2 more
openaire   +2 more sources

Robust Spot Melting by 3D Spot Arrangements in Electron Beam Powder Bed Fusion

Advanced Engineering Materials, EarlyView.
This work proposes an approach to replace separately melted contours for spot melting in electron beam powder fusion. Adapting the spot arrangements close to the contour combined with stacking yields a comparable surface quality without the inherent challenges of separate contours, as demonstrated, by electron optical images and roughness measurements.
Tobias Kupfer, Lukas Spano, Sebastian Pohl, Carolin Körner, Matthias Markl   +4 more
wiley   +1 more source

Performance of Clustering on ANFIS for Weather Forecasting

CommIT Journal, 2018
This paper proposes the comparison of using K-Means and Fuzzy C-Means (FCM) to optimize the premise parameters on Adaptive Neuro-Fuzzy Inference System (ANFIS) for weather forecasting.
Candra Dewi
doaj   +1 more source

Weighted-covariance factor fuzzy C-means clustering [PDF]

, 2015
In this paper, we propose a factor weighted fuzzy c-means clustering algorithm. Based on the inverse of a covariance factor, which assesses the collinearity between the centers and samples, this factor takes also into account the compactness of the ...
Bertrand, Isabelle, Chabbert, Brigitte, Perrin, Eric, Rammal, Abbas, Vrabie, Valériu   +4 more
core   +2 more sources

Benchmarking parameterized fuzzy c-Means classifier

2009 IEEE International Conference on Fuzzy Systems, 2009
This paper reports on the performance of the fuzzy c-means based classifier (FCMC). Test set performances optimized by way of several CV procedures and three sets of hyperparameters are throughly compared. UCI benchmark datasets are used to evaluate the performance.
Kazuya Nagaura, Hidetomo Ichihashi, Akira Notsu, Katsuhiro Honda   +3 more
openaire   +2 more sources

Multimodal Data‐Driven Microstructure Characterization

Advanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

A Lightweight Procedural Layer for Hybrid Experimental–Computational Workflows in Materials Science

Advanced Engineering Materials, EarlyView.
We unveil a prototype hybrid‐workflow framework that fuses automatedcomputation with hands‐on experiments. Built atop pyiron, a lightweight, parameterized layer translates procedure descriptions into executable manual steps, syncing instrument settings, human interventions, and data capture in real‐time today.
Steffen Brinckmann, Sarath Menon, Raphael Röske, Johannes Steinhülb, Michael Selzer, Jan Janssen, Tilmann Hickel, Ruth Schwaiger, Jörg Neugebauer   +8 more
wiley   +1 more source

KLASTERING INDUSTRI DI KABUPATEN KUDUS MENGGUNAKAN METODE FUZZY C-MEANS

Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer, 2016
Penelitian ini menggunakan metode klastering Fuzzy C Means, yang digunakan untuk klastering industri di Kabupaten Kudus, teori ini merupakan penggunaan dari teori klastering Fuzzy C Means. Klastering industri di kabupaten Kudus dilaksanakan sebagai upaya
Pratomo Setiaji, Wiwit Agus Triyanto
doaj   +1 more source