Computational intelligence techniques especially neural networks have been attracting a large number of researchers' attentions in the past three decades. It has been well known that conventional learning methods on neural networks have apparent drawbacks and limitations including: (1) slow learning speed, (2) trivial human tuned parameters, and (3) complicated learning algorithms. Extreme Lear...

Extreme Learning Machine (ELM) represents a popular paradigm for training feedforward neural networks due to its fast learning time. This paper applies the technique for the automatic classification of speech utterances. Power Normalized Cepstral Coefficients (PNCC) are employed as feature vectors and ELM performs the final classification. Both the baseline ELM algorithm and ELM with kernel hav...

This paper is focused on Fuzzy Extreme Learning Machine (ELM) algorithm based field oriented control system for induction motor fed by Matrix Converter drive. The use of fuzzy ELM algorithm based ANN Controllers in the FOC system reduces the computation time. The controller is used to compute the appropriate set of switching voltage vectors for matrix converter to achieve the maximum efficiency...

This paper presents an Extreme Learning Machine (ELM) approach for a fast and accurate estimation of the power system loading margin for multiple contingencies with reduced input attributes. Active and reactive power flows of all load buses are chosen as the input features to the ELM. The training data for the ELM model are generated by using the Continuation Power Flow (CPF) method. The propos...

In order to overcome the problems of poor understandability of the pattern recognition-based transient stability assessment (PRTSA) methods, a new rule extraction method based on extreme learning machine (ELM) and an improved Ant-miner (IAM) algorithm is presented in this paper. First, the basic principles of ELM and Ant-miner algorithm are respectively introduced. Then, based on the selected o...

This paper discusses the performance of a novel Coral Reefs Optimization – Extreme Learning Machine (CRO–ELM) algorithm in a real problem of global solar radiation prediction. The work considers different meteorological data from the radiometric station at Murcia (southern Spain), both from measurements, radiosondes and meteorological models, and fully describes the hybrid CRO–ELM to solve the ...

Rapid bifurcations in the plasma response to slowly varying n=2 magnetic fields are observed as the plasma transitions into and out of edge-localized mode (ELM) suppression. The rapid transition to ELM suppression is characterized by an increase in the toroidal rotation and a reduction in the electron pressure gradient at the top of the pedestal that reduces the perpendicular electron flow ther...

The extreme learning machines (ELMs) have been proposed for generalized single-hidden-layer feedforward networks (SLFNs) which need not be neuron alike and perform well in both regression and classification applications. An active topic in ELMs is how to automatically determine network architectures for given applications. In this paper, we propose an extreme learning machine with adaptive grow...

Local Coupled Extreme Learning Machine (LCELM) is a recently-proposed variant of ELM, which assigns an address for each hidden-layer node and activates the hidden-layer node when its activated degree is less than a given threshold. In this paper, an improved version of LCELM is proposed by developing a new way to initialize the address for each hidden-layer node and calculating the activated de...