AIMC Topic: Fuzzy Logic

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HCF-CRS: A Hybrid Content based Fuzzy Conformal Recommender System for providing recommendations with confidence.

PloS one
A Recommender System (RS) is an intelligent system that assists users in finding the items of their interest (e.g. books, movies, music) by preventing them to go through huge piles of data available online. In an effort to overcome the data sparsity ...

Incorporating EBO-HSIC with SVM for Gene Selection Associated with Cervical Cancer Classification.

Journal of medical systems
Microarray technology is utilized by the biologists, in order to compute the expression levels of thousands of genes. Cervical cancer classification utilizing gene expression data depends upon conventional supervised learning methods, wherein only la...

An Approach to Determining Attribute Weights Based on Integrating Preference Information on Attributes with Decision Matrix.

Computational intelligence and neuroscience
The interval multiple attribute decision-making problems are studied in this paper, where the preference information on attributes is expressed with preference orderings, linguistic terms, interval numbers, and inequality constraints among partial at...

Laplacian mixture modeling for network analysis and unsupervised learning on graphs.

PloS one
Laplacian mixture models identify overlapping regions of influence in unlabeled graph and network data in a scalable and computationally efficient way, yielding useful low-dimensional representations. By combining Laplacian eigenspace and finite mixt...

An improved stability result for delayed Takagi-Sugeno fuzzy Cohen-Grossberg neural networks.

Neural networks : the official journal of the International Neural Network Society
This work proposes a novel and improved delay independent global asymptotic stability criterion for delayed Takagi-Sugeno (T-S) fuzzy Cohen-Grossberg neural networks exploiting a suitable fuzzy-type Lyapunov functional in the presence of the nondecre...

Registration-Based Organ Positioning and Joint Segmentation Method for Liver and Tumor Segmentation.

BioMed research international
The automated segmentation of liver and tumor from CT images is of great importance in medical diagnoses and clinical treatment. However, accurate and automatic segmentation of liver and tumor is generally complicated due to the complex anatomical st...

Initial state perturbations as a validation method for data-driven fuzzy models of cellular networks.

BMC bioinformatics
BACKGROUND: Data-driven methods that automatically learn relations between attributes from given data are a popular tool for building mathematical models in computational biology. Since measurements are prone to errors, approaches dealing with uncert...

Fuzzy Group Consensus Decision Making and Its Use in Selecting Energy-Saving and Low-carbon Technology Schemes in Star Hotels.

International journal of environmental research and public health
Energy-saving and low-carbon technologies play important roles in reducing environmental risk and developing green tourism. An energy-saving and low-carbon technology scheme selection may often involve multiple criteria and sub-criteria as well as mu...

Detecting gene-gene interactions for complex quantitative traits using generalized fuzzy classification.

BMC bioinformatics
BACKGROUND: Quantitative traits or continuous outcomes related to complex diseases can provide more information and therefore more accurate analysis for identifying gene-gene and gene- environment interactions associated with complex diseases. Multif...

Bounded Fuzzy Possibilistic Method Reveals Information about Lung Cancer through Analysis of Metabolomics.

IEEE/ACM transactions on computational biology and bioinformatics
Learning methods, such as conventional clustering and classification, have been applied in diagnosing diseases to categorize samples based on their features. Going beyond clustering samples, membership degrees represent to what degree each sample bel...