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The multi-fuzzy N-soft set and its applications to decision-making
The goal of this paper is to introduce a novel hybrid model called multi-fuzzy N-soft set, and
to design an adjustable decision-making methodology for solving problems where the inputs …
to design an adjustable decision-making methodology for solving problems where the inputs …
FP-intuitionistic multi fuzzy N-soft set and its induced FP-Hesitant N soft set in decision-making
Intuitionistic fuzzy sets (IFSs) can effectively represent and simulate the uncertainty and
diversity of judgment information offered by decision-makers (DMs). In comparison to fuzzy …
diversity of judgment information offered by decision-makers (DMs). In comparison to fuzzy …
IFP-intuitionistic multi fuzzy N-soft set and its induced IFP-hesitant N-soft set in decision-making
Intuitionistic fuzzy sets (IFSs) can effectively represent and simulate the uncertainty and
diversity of judgment information offered by decision-makers (DMs). In comparison to fuzzy …
diversity of judgment information offered by decision-makers (DMs). In comparison to fuzzy …
Bounded multivariate generalized Gaussian mixture model using ICA and IVA
A bounded multivariate generalized Gaussian mixture model with a full covariance matrix is
proposed for modeling data in a bounded support region. For model selection, we propose …
proposed for modeling data in a bounded support region. For model selection, we propose …
Ica and iva bounded multivariate generalized gaussian mixture based hidden markov models
Abstract Machine learning (ML), a branch of artificial intelligence (AI), is an area of
computational science that is concerned with the analysis and interpretation of patterns and …
computational science that is concerned with the analysis and interpretation of patterns and …
Novel approach for ECG separation using adaptive constrained IVABMGGMM
In this paper, we introduce the constrained independent vector analysis integrated with the
bounded multivariate generalized Gaussian mixture model (cIVABMGGMM) to tackle the …
bounded multivariate generalized Gaussian mixture model (cIVABMGGMM) to tackle the …
[HTML][HTML] Unsupervised Mixture Models on the Edge for Smart Energy Consumption Segmentation with Feature Saliency
Smart meter datasets have recently transitioned from monthly intervals to one-second
granularity, yielding invaluable insights for diverse metering functions. Clustering analysis, a …
granularity, yielding invaluable insights for diverse metering functions. Clustering analysis, a …
Automatic music mood classification using multi-modal attention framework
Automatic music recommendation systems based on human emotions are becoming
popular nowadays. Since audio and lyrics can provide a rich set of information regarding a …
popular nowadays. Since audio and lyrics can provide a rich set of information regarding a …
Multivariate bounded support Laplace mixture model
In this paper, bounded Laplace mixture model (BLMM) is proposed. The parameters of
proposed model are estimated by maximum likelihood approach via expectation …
proposed model are estimated by maximum likelihood approach via expectation …
Multivariate‐bounded Gaussian mixture model with minimum message length criterion for model selection
Bounded support Gaussian mixture model (BGMM) has been proposed for data modelling
as an alternative to unbounded support mixture models for the cases when the data lies in …
as an alternative to unbounded support mixture models for the cases when the data lies in …