Background: selecting the correct statistical test and data mining method depends highly on the measurement scale of data, type of variables, and purpose of the analysis. Different …
KP Lin - IEEE Transactions on Fuzzy systems, 2013 - ieeexplore.ieee.org
This study proposes a novel evolutionary kernel intuitionistic fuzzy c-means clustering algorithm (EKIFCM) that combines Atanassov's intuitionistic fuzzy sets (IFSs) with kernel …
A Mekhmoukh, K Mokrani - Computer methods and programs in …, 2015 - Elsevier
In this paper, a new image segmentation method based on Particle Swarm Optimization (PSO) and outlier rejection combined with level set is proposed. A traditional approach to the …
N Kumar, H Kumar - Data & Knowledge Engineering, 2022 - Elsevier
Fuzzy clustering is a well-established technique among the well-known clustering techniques in several real-world applications due to easy implementation and produces …
J Chan, S Parameswaran - 17th International Conference on …, 2004 - ieeexplore.ieee.org
In this paper, we describe NoCGEN, a Network On Chip (NoC) generator, which is used to create a simulatable and synthesizable NoC description. NoCGEN uses a set of …
Recognition and mapping of mineralization-related patterns in geochemical data is a key computational analysis to achieve a predictive model of prospectivity for mineral deposit …
Recommender system (RS) is an emerging technique in information retrieval to handle a large amount of online data effectively. It provides recommendation to the online user in …
This paper proposes an enhanced discriminability recurrent fuzzy neural network for temporal classification problems. To consider classification problems, the most important …
Objective: In this study we propose a fuzzy classifier whose rule antecedents are determined based on the new approach to Clustering with Pairs of Prototypes (CPP). After …