Journal ArticleDOI
A New Cluster Validity Index for Fuzzy Clustering
TLDR
A new “Graded Distance index” (GD_index) is proposed for computing optimal number of fuzzy clusters for a given data set and the efficiency of this index is compared with well-known existing indices and tested on several data sets.About:
This article is published in IFAC Proceedings Volumes.The article was published on 2013-12-01. It has received 21 citations till now. The article focuses on the topics: Fuzzy clustering & Cluster analysis.read more
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Journal ArticleDOI
Clustering Algorithms: Their Application to Gene Expression Data
Jelili Oyelade,Itunuoluwa Isewon,Funke Oladipupo,Olufemi Aromolaran,Efosa Uwoghiren,Faridah Ameh,Moses Achas,Ezekiel Adebiyi +7 more
TL;DR: This review examines the various clustering algorithms applicable to the gene expression data in order to discover and provide useful knowledge of the appropriate clustering technique that will guarantee stability and high degree of accuracy in its analysis procedure.
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An Evolutionary Neuro-Fuzzy C-means Clustering Technique
TL;DR: A Neuro-Fuzzy C-Means Clustering algorithm (NFCM) is presented to resolve the issues mentioned above by adopting a novel Artificial Neural Network (ANN) based clustering approach.
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Green Energy in Central and Eastern European (CEE) Countries: New Challenges on the Path to Sustainable Development
TL;DR: In this paper, the authors classified the Central and Eastern European (CEE) countries from the point of view of green energy transformation (original indicator) and to predict new threats to Romania, Poland, and Bulgaria.
Journal ArticleDOI
Multi-Objective Optimized Fuzzy Clustering for Detecting Cell Clusters from Single-Cell Expression Profiles
Saurav Mallik,Zhongming Zhao +1 more
TL;DR: A multi-objective optimization-based fuzzy clustering approach for detecting cell clusters from scRNA-seq data that obtained differentially expressed genes (DEGs) using Limma through the comparison of expression of the samples between each resultant cluster and the remaining clusters.