Extreme learning machine (ELM) is a training algorithm for single hidden layer feedforward
neural network (SLFN), which converges much faster than traditional methods and yields …

Extreme learning machine (ELM) has gained increasing interest from various research fields
recently. In this review, we aim to report the current state of the theoretical research and …

Recently, the feed-forward neural network is functioning with slow computation time and
increased gain. The weight vector and biases in the neural network can be tuned based on …

Chronic kidney disease (CKD) is a global health problem with high morbidity and mortality
rate, and it induces other diseases. Since there are no obvious symptoms during the early …

Developing simple and accurate state estimators for battery packs is important but
technically challenging due to not only the high number of batteries requiring monitoring but …

Due to the simplicity of their implementations, least square support vector machine (LS-
SVM) and proximal support vector machine (PSVM) have been widely used in binary …

Urban energy use modeling is important for understanding and managing energy
performance in cities. However, the existing methods and tools have limitations in …

Computational intelligence techniques have been used in wide applications. Out of
numerous computational intelligence techniques, neural networks and support vector …

Extreme learning machine (ELM) is a new learning algorithm for the single hidden layer
feedforward neural networks. Compared with the conventional neural network learning …

This paper proposes a multivariate chaotic Extreme Learning Machine (ELM) model for the
prediction of the displacement of reservoir landslides. The displacement time series of the …