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RISPredicting Corporate Financial Distress Using Data Mining Techniques An Application in Tehran Stock Exchange
to predict financial distress of Iranian firms, with four techniques: support vector machines, artificial neural networks (ANN), k-nearest neighbor and naïve bayesian classifier by using accounting information of the firms for two years prior to financial...
POD utilization methods for STATCOMs
QRS complex detection based on simple robust 2-D pictorial-geometrical feature
to each image for establishment of an appropriate feature space. Afterwards the K-Nearest Neighbors (KNN), Artificial Neural Network (ANN) and Adaptive
Network Fuzzy Inference Systems (ANFIS) were designed and implemented to the ECG signal...
Accurate Single Phase Fault Location Method for Transmission Lines based on K-nearest Neighbor Algorithm using One-end Voltage
In this paper, some useful features are extracted
from voltage signals measured at one terminal of the transmission
line, which are highly efficient for accurate fault locating. These
features are ...
Large symmetric margin instance selection algorithm
In instance-based classifiers, there is a need for storing a large number of samples as a training set. In this paper, we propose a large symmetric margin instance selection algorithm, namely LAMIS. LAMIS removes non-border ...
A novel anomaly detection method based on adaptive Mahalanobis-squared distance and one-class kNN rule for structural health monitoring under environmental effects
Anomaly detection by Mahalanobis-squared distance (MSD) is a popular unsupervised learning approach to structural health monitoring (SHM). Despite the popularity and high applicability of the MSD-based anomaly detection ...