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Membership Adjusted Superpixel Based Fuzzy C-Means for White Blood Cell Segmentation
Fuzzy C-means (FCM) is a well-known clustering technique that is efficiently used for image segmentation. However, the performance of the FCM...
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Viewpoint-Driven Subspace Fuzzy C-Means Algorithm
Most of the current fuzzy clustering algorithms are sensitive to cluster initialization and do not cope well with high dimensionality. To alleviate...
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Optimization of Fuzzy C-Means with Alternating Direction Method of Multipliers
Among the clustering methods, K-Means and its variants are very popular. These methods solve at each iteration the first-order optimality conditions....
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Software cost estimation model based on fuzzy C-means and improved self adaptive differential evolution algorithm
In the current scenario, one of the main challenges faced by many organizations is to accurately predict effort and cost estimation during software...
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LapEFCM: overlap** community detection using laplacian eigenmaps and fuzzy C-means clustering
The explosion of research in the field of network science has seen enormous growth in detection of communities. Since communities are not always...
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Multi-stage glioma segmentation for tumour grade classification based on multiscale fuzzy C-means
Segmentation of the brain glioma tumour sub-regions is critical to diagnosis and prognosis in clinical applications. This paper proposes a...
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A Hybrid Model Integrating Improved Fuzzy c-means and Optimized Mixed Kernel Relevance Vector Machine for Classification of Coal and Gas Outbursts
The class labels of collected coal and gas outbursts sample data may be wrong, if these collected sample data are directly used for outbursts...
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Local search genetic algorithm-based possibilistic weighted fuzzy c-means for clustering mixed numerical and categorical data
Clustering for mixed numerical and categorical attributes has attracted many researchers due to its necessity in many real-world applications. One...
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Strategic real time framework for healthcare using fuzzy C-means systems
Having enhancement of automation of sensor, huge information such as the big data are examined and has become yet another worldview for huge scope of...
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Adaptive type2-possibilistic C-means clustering and its application to microarray datasets
Microarray technology is an important innovation that simultaneously facilitates measuring the expression level for thousands of genes in different...
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Fuzzy C-Means Clustering of Network for Multi Mobile Agent Itinerary Planning
Mobile agent (MA) works potentially efficiently in reducing network bandwidth consumption for distributed computing. In an MA-based system, a...
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Performance Enhancement in WSN Through Fuzzy C-Means Based Hybrid Clustering (FCMHC)
The researches in Wireless Sensor Networks (WSNs) strive for the efficient data transmission with optimized lifetime of the system. Load Balanced...
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TL-FCM: A hierarchical prediction model based on two-level fuzzy c-means clustering for bike-sharing system
In recent years, shared bikes have gradually emerged into public life as a new way to travel and helped solve the last-mile problem of residents’...
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Parallel hesitant fuzzy C-means algorithm to image segmentation
Hesitant fuzzy information allows clustering data with multiple possible membership values for a single item in a reference set. Hesitant fuzzy sets...
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Pythagorean Fuzzy c-means Clustering Algorithm
This article presents algorithm for \(c\) -means...
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Kernel Subspace Possibilistic Fuzzy C-Means Algorithm Driven by Feature Weights
At present, one of the difficulties in the field of fuzzy clustering is the clustering analysis for high dimensional data. Most of the existing fuzzy...
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Spatial Rough Intuitionistic Fuzzy C-Means Clustering for MRI Segmentation
Medical image segmentation is the challenging problem in real-time applications due to the occurrence of noise and uncertainties between different...
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Privacy Preserving of Two Collaborating Parties Using Fuzzy C-Means Clustering
In this smart and rapidly growing computing world, most of the organizations and companies needs to share necessary information (data) to third...
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A new weighted fuzzy C-means clustering for workload monitoring in cloud datacenter platforms
The rapid growth in virtualization solutions has driven the widespread adoption of cloud computing paradigms among various industries and...
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Lung Cancer Detection Using Modified Fuzzy C-Means Clustering and Adaptive Neuro-Fuzzy Network
Air Pollution is responsible for many diseases and death happening all around the world. The Particulate Matter (PM) present in the air is...