A survey on nature inspired metaheuristic algorithms for partitional clustering
The partitional clustering concept started with K-means algorithm which was published in
1957. Since then many classical partitional clustering algorithms have been reported based …
1957. Since then many classical partitional clustering algorithms have been reported based …
Image analysis operations applied to hyperspectral images for non-invasive sensing of food quality–a comprehensive review
GM ElMasry, S Nakauchi - Biosystems engineering, 2016 - Elsevier
Highlights•Describing fundamental configuration and working principles of hyperspectral
systems.•The paper underscores the theoretical and practical issues of hyperspectral …
systems.•The paper underscores the theoretical and practical issues of hyperspectral …
Automatic clustering using nature-inspired metaheuristics: A survey
A José-García, W Gómez-Flores - Applied Soft Computing, 2016 - Elsevier
In cluster analysis, a fundamental problem is to determine the best estimate of the number of
clusters; this is known as the automatic clustering problem. Because of lack of prior domain …
clusters; this is known as the automatic clustering problem. Because of lack of prior domain …
Adaptive k-means clustering algorithm for MR breast image segmentation
Image segmentation is vital for meaningful analysis and interpretation of the medical
images. The most popular method for clustering is k-means clustering. This article presents …
images. The most popular method for clustering is k-means clustering. This article presents …
Multi-objective grey wolf optimizer for improved cervix lesion classification
Cervical cancer is one of the vital and most frequent cancers, but can be cured effectively if
diagnosed in the early stage. This is a novel effort towards effective characterization of cervix …
diagnosed in the early stage. This is a novel effort towards effective characterization of cervix …
Fuzzy granular gravitational clustering algorithm for multivariate data
A new method for finding fuzzy information granules from multivariate data through a
gravitational inspired clustering algorithm is proposed in this paper. The proposed algorithm …
gravitational inspired clustering algorithm is proposed in this paper. The proposed algorithm …
Color image segmentation based on multiobjective artificial bee colony optimization
This paper presents a new color image segmentation method based on a multiobjective
optimization algorithm, named improved bee colony algorithm for multi-objective …
optimization algorithm, named improved bee colony algorithm for multi-objective …
A novel fuzzy similarity measure and prevalence estimation approach for similarity profiled temporal association pattern mining
V Radhakrishna, SA Aljawarneh, PV Kumar… - Future generation …, 2018 - Elsevier
Abstract Data generated from Sensors, IoT environment and many real time applications is
mainly spatial, temporal, or spatio-temporal. Some of them include data generated from …
mainly spatial, temporal, or spatio-temporal. Some of them include data generated from …
Discovering residential electricity consumption patterns through smart-meter data mining: A case study from China
K Zhou, C Yang, J Shen - Utilities Policy, 2017 - Elsevier
With the increasing penetration of information and communication technologies (ICTs) in
energy systems, traditional energy systems are being digitized. Advanced analysis of the …
energy systems, traditional energy systems are being digitized. Advanced analysis of the …
A Self‐Adaptive Fuzzy c‐Means Algorithm for Determining the Optimal Number of Clusters
M Ren, P Liu, Z Wang, J Yi - Computational intelligence and …, 2016 - Wiley Online Library
For the shortcoming of fuzzy c‐means algorithm (FCM) needing to know the number of
clusters in advance, this paper proposed a new self‐adaptive method to determine the …
clusters in advance, this paper proposed a new self‐adaptive method to determine the …