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Going Concern Prediction of Iranian Companies by Using Fuzzy C-Means
Decision-making problems in the area of financial status evaluation have been considered very important. Making in- correct decisions in firms is very likely to cause financial crises and distress. Predicting going concern ...
Research on the field coverage generated by antennas in confined space
Generalized Fuzzy C-Means Clustering with Improved Fuzzy Partitions and Shadowed Sets
Clustering involves grouping data points together according to some measure of similarity. Clustering is one of the most significant unsupervised learning problems and do not need any labeled data. There are many clustering ...
Financial Distress Prediction of Iranian Companies by Using Data Mining Techniques
the prediction accuracy of SVDD, we compare its performance with fuzzy c-means (FCM).The experiment results show that SVDD outperforms the other method.
The data used in this research was obtained from Iran Stock Market and Accounting Research Database...
An efficient approach for unsupervised fuzzy clustering based on grouping evolution strategies
approach is validated through using several data sets and results are compared with those of fuzzy c-means algorithm, particle swarm optimization algorithm (PSO), differential evolution (DE) and league championship algorithm (LCA). We also investigate...
Vector Fuzzy C-means
Many variants of fuzzy c-means (FCM) clustering method are applied to crisp numbers but only a few of them are
extended to non-crisp numbers, mainly due to the fact that the latter needs complicated equations and exhausting calculations...