Knowledge-based energy investments of European economies and policy recommendations for sustainable development
This study evaluates the knowledge-based energy investments of European economies. For
this purpose, a novel hybrid fuzzy decision-making model is generated to define important …
this purpose, a novel hybrid fuzzy decision-making model is generated to define important …
Pixel and region level information fusion in membership regularized fuzzy clustering for image segmentation
Membership regularized fuzzy clustering methods apply an important prior that neighboring
data points should possess similar memberships according to an affinity/similarity matrix. As …
data points should possess similar memberships according to an affinity/similarity matrix. As …
Density-based IFCM along with its interval valued and probabilistic extensions, and a review of intuitionistic fuzzy clustering methods
Fuzzy clustering has been useful in capturing the uncertainty present in the data during
clustering. Most of the c-Means algorithms such as FCM (Fuzzy c-Means), IFCM …
clustering. Most of the c-Means algorithms such as FCM (Fuzzy c-Means), IFCM …
Robust self-sparse fuzzy clustering for image segmentation
Traditional fuzzy clustering algorithms suffer from two problems in image segmentations.
One is that these algorithms are sensitive to outliers due to the non-sparsity of fuzzy …
One is that these algorithms are sensitive to outliers due to the non-sparsity of fuzzy …
AFCM-LSMA: New intelligent model based on Lévy slime mould algorithm and adaptive fuzzy C-means for identification of COVID-19 infection from chest X-ray …
Problem A worldwide challenge is to provide medical resources required for COVID-19
detection. They must be effective tools for fast detection and diagnose of the virus using a …
detection. They must be effective tools for fast detection and diagnose of the virus using a …
[HTML][HTML] Gaussian-based hybrid approach to Entropy for analyzing energy efficiency of emerging economies
This study aims to evaluate energy efficiency in emerging economies. Within this context, a
hybrid fuzzy multi-criteria decision-making (MCDM) model is generated. In this model, firstly …
hybrid fuzzy multi-criteria decision-making (MCDM) model is generated. In this model, firstly …
Coordinated control system modeling of ultra-supercritical unit based on a new fuzzy neural network
G Hou, J Xiong, G Zhou, L Gong, C Huang, S Wang - Energy, 2021 - Elsevier
The coordinated control systems (CCS) in ultra-supercritical thermal power unit, like many
other industrial systems, is a complex multivariable system with severe nonlinearity, strong …
other industrial systems, is a complex multivariable system with severe nonlinearity, strong …
Fast and robust spatial fuzzy bounded k-plane clustering method for human brain MRI image segmentation
Fuzzy k-plane clustering (FkPC) is a soft plane-based clustering that efficiently clusters non-
spherically distributed data. However, the FkPC method is sensitive to noise and provides …
spherically distributed data. However, the FkPC method is sensitive to noise and provides …
A type-2 neutrosophic-entropy-fusion based multiple thresholding method for the brain tumor tissue structures segmentation
P Singh - Applied Soft Computing, 2021 - Elsevier
In this paper, we introduce an extension theory of the neutrosophic set (NS) called type-2
neutrosophic set (T2NS). This new theory provides a granular representation of features and …
neutrosophic set (T2NS). This new theory provides a granular representation of features and …
[HTML][HTML] Classification and intuitionistic fuzzy set based software bug triaging techniques
RR Panda, NK Nagwani - Journal of King Saud University-Computer and …, 2022 - Elsevier
Software development is a modular approach involving multiple developers and multi-
tasking teams working at different locations. A particular term in a software bug can belong …
tasking teams working at different locations. A particular term in a software bug can belong …