Evolved-Cooperative Correntropy-Based Extreme Learning Machine for Robust Prediction

A Robust Online Sequential Extreme Learning Machine

A Robust and Regularized Extreme Learning Machine

In a moment when the study of outlier robustness within Extreme Learning Machine is still in its infancy, we propose a method that combines maximization of the hidden layer’s information transmission, through Batch Intrinsic Plasticity (BIP), with robust estimation of the output weights. This method named R-ELM/BIP generates a reliable solution in the presence of corrupted data with a good gene...

Software Aging Prediction based on Extreme Learning Machine

In the research on software aging and rejuvenation, one of the most important questions is when to trigger the rejuvenation action. And it is useful to predict the system resource utilization state efficiently for determining the rejuvenation time. In this paper, we propose software aging prediction model based on extreme learning machine (ELM) for a real VOD system. First, the data on the para...

Simulation of Scour Pattern Around Cross-Vane Structures Using Outlier Robust Extreme Learning Machine

In this research, the scour hole depth at the downstream of cross-vane structures with different shapes (i.e., J, I, U, and W) was simulated utilizing a modern artificial intelligence method entitled "Outlier Robust Extreme Learning Machine (ORELM)". The observational data were divided into two groups: training (70%) and test (30%). Then, using the input parameters including the ratio of the st...

Cancer Classification by Correntropy-Based Sparse Compact Incremental Learning Machine

Cancer prediction is of great importance and significance and it is crucial to provide researchers and scientists with novel, accurate and robust computational tools for this issue. Recent technologies such as Microarray and Next Generation Sequencing have paved the way for computational methods and techniques to play critical roles in this regard. Many important problems in cell biology requir...