A Novel Robust Online Extreme Learning Machine for the Non-Gaussian Noise

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...

ROS-ELM: A Robust Online Sequential Extreme Learning Machine for Big Data Analytics

In this paper, a robust online sequential extreme learning machine (ROS-ELM) is proposed. It is based on the original OS-ELM with an adaptive selective ensemble framework. Two novel insights are proposed in this paper. First, a novel selective ensemble algorithm referred to as particle swarm opt imization selective ensemble (PSOSEN) is proposed. Noting that PSOSEN is a general selective ensembl...

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...

A Novel Online Sequential Extreme Learning Machine for Gas Utilization Ratio Prediction in Blast Furnaces

Gas utilization ratio (GUR) is an important indicator used to measure the operating status and energy consumption of blast furnaces (BFs). In this paper, we present a soft-sensor approach, i.e., a novel online sequential extreme learning machine (OS-ELM) named DU-OS-ELM, to establish a data-driven model for GUR prediction. In DU-OS-ELM, firstly, the old collected data are discarded gradually an...