Fuzzy C-means (FCM) clustering algorithm: a decade review from 2000 to 2014
The Fuzzy c-means is one of the most popular ongoing area of research among all types of
researchers including Computer science, Mathematics and other areas of engineering, as …
researchers including Computer science, Mathematics and other areas of engineering, as …
Two levels decision system for efficient planning and implementation of bioenergy production
N Ayoub, R Martins, K Wang, H Seki, Y Naka - Energy conversion and …, 2007 - Elsevier
When planning bioenergy production from biomass, planners should take into account each
and every stakeholder along the biomass supply chains, eg biomass resources suppliers …
and every stakeholder along the biomass supply chains, eg biomass resources suppliers …
Fuzzy and hard clustering analysis for thyroid disease
AT Azar, SA El-Said, AE Hassanien - Computer methods and programs in …, 2013 - Elsevier
Thyroid hormones produced by the thyroid gland help regulation of the body's metabolism. A
variety of methods have been proposed in the literature for thyroid disease classification. As …
variety of methods have been proposed in the literature for thyroid disease classification. As …
FCM Clustering Approach Optimization Using Parallel High‐Speed Intel FPGA Technology
Fuzzy C‐Means (FCM) is a widely used clustering algorithm that performs well in various
scientific applications. Implementing FCM involves a massive number of computations, and …
scientific applications. Implementing FCM involves a massive number of computations, and …
[PDF][PDF] A review on suppressed fuzzy c-means clustering models
Suppressed fuzzy c-means clustering was proposed as an attempt to combine the better
properties of hard and fuzzy c-means clustering, namely the quicker convergence of the …
properties of hard and fuzzy c-means clustering, namely the quicker convergence of the …
Accelerating FCM algorithm using high-speed FPGA reconfigurable computing architecture
Abstract Fuzzy C-Means (FCM) algorithm is a clustering algorithm that is frequently used to
enhance the detection accuracy for different applications. However, FCM is a high …
enhance the detection accuracy for different applications. However, FCM is a high …
Risk assessment of meteo-groundwater drought using copula approach in the arid region
JB Meimandi, O Bazrafshan, Y Esmaeilpour… - … Research and Risk …, 2024 - Springer
Groundwater serves as the primary source of freshwater in arid and semi-arid regions,
rendering them resilient against precipitation scarcity. Various aspects of the drought …
rendering them resilient against precipitation scarcity. Various aspects of the drought …
Generalization rules for the suppressed fuzzy c-means clustering algorithm
L Szilágyi, SM Szilágyi - Neurocomputing, 2014 - Elsevier
Intending to achieve an algorithm characterized by the quick convergence of hard c-means
(HCM) and finer partitions of fuzzy c-means (FCM), suppressed fuzzy c-means (s-FCM) …
(HCM) and finer partitions of fuzzy c-means (FCM), suppressed fuzzy c-means (s-FCM) …
[HTML][HTML] Spatial delineation on marine environmental characteristics using fuzzy c-means clustering method
BACKGROUND AND OBJECTIVES: Conservation efforts are often prioritized on a large
spatial scale because information about local ecosystems is frequently lacking. Therefore …
spatial scale because information about local ecosystems is frequently lacking. Therefore …
Analytical and numerical evaluation of the suppressed fuzzy c-means algorithm: a study on the competition in c-means clustering models
Suppressed fuzzy c-means (s-FCM) clustering was introduced in Fan et al.(Pattern Recogn
Lett 24: 1607–1612, 2003) with the intention of combining the higher speed of hard c-means …
Lett 24: 1607–1612, 2003) with the intention of combining the higher speed of hard c-means …