Companies and industries are faced with a huge amount of raw data, which have
information and knowledge in their hidden layer. Also, the format, size, variety, and velocity …

In this study, the cyclic of a spark ignition engine using octane fuel is modeled using extreme
learning machine, an emergent technology related to single-hidden layer feedforward …

Due to the inefficiency of gradient-based iterative ways in network training, randomization-
based neural networks usually offer non-iterative closed form solutions. The random vector …

Recent advances in remote sensing techniques allow for the collection of hyperspectral
images with enhanced spatial and spectral resolution. In many applications, these images …

A hybridized image classification strategy is proposed based on discrete wavelet transform,
artificial bee colony (ABC) and extreme learning machine (ELM). The proposed …

One important strategy in semi-supervised learning is to utilize the predicted pseudo labels
of unlabeled data to relieve the overdependence on the ground truth of supervised learning …

For regression tasks, the existing extreme learning machine (ELM) and kernel extreme
learning machine (KELM) algorithms exhibit singularity and over-fitting problems when the …

Ordinal regression is a special kind of machine learning problem, which aims to label
patterns with an ordinal scale. Due to the ubiquitous existence of the ordering information in …

Most existing state-of-the-art deep learning algorithms discover sophisticated
representations in huge datasets using convolutional neural networks (CNNs) that mainly …

Abstract Random Vector Functional Link (RVFL) is a widely used learning technique due to
its less computational complexity, fast learning speed, and ease of implementation …