Profound attention to MapReduce framework has been caught by many different areas. It is
presently a practical model for data-intensive applications due to its simple interface of …

Extreme learning machine (ELM) is a novel and recent machine learning algorithm which
was first proposed by Huang et al.(Proceedings of 2004 IEEE international joint conference …

As data sets become larger and more complicated, an extreme learning machine (ELM) that
runs in a traditional serial environment cannot realize its ability to be fast and effective …

Wind speed forecasting with artificial neural networks (ANNs) plays important role in safely
utilizing and integrating the wind power. With the rapid updated wind speed data, however …

Mining with big data or big data mining has become an active research area. It is very
difficult using current methodologies and data mining software tools for a single personal …

Abstract The previous Fuzzy Rule-Based Classification Systems (FRBCSs) for Big Data
problems consist in concurrently learning multiple Chi et al. FRBCSs whose rule bases are …

A dynamic adjustment kernel extreme learning machine with transfer functions is proposed
for parametric modeling of the electromagnetic behavior of microwave components. If …

To address the problem that the faults in axial piston pumps are complex and difficult to
effectively diagnose, an integrated hydraulic pump fault diagnosis method based on the …

Emergence of extreme learning machine as a breakneck learning algorithm has marked its
prominence in solitary hidden layer feed-forward networks. Kernel-based extreme learning …

Heterogeneous big data poses many challenges in machine learning. Its enormous scale,
high dimensionality, and inherent uncertainty make almost every aspect of machine learning …