In this paper, we review our work for forecasting hourly global horizontal solar radiation
based on the combination of unsupervised k-means clustering algorithm and artificial neural …

Collaboration enables weak species to survive in an environment where different species
compete for limited resources. Cooperative coevolution (CC) is a nature-inspired …

This paper presents bearing fault diagnosis using the image classification of different fault
patterns. Feature extraction for image classification is carried out using a novel approach of …

This paper proposes a learning framework for single-hidden layer feedforward neural
networks (SLFN) called optimized extreme learning machine (O-ELM). In O-ELM, the …

Changes in geomagnetic conditions have been shown to affect the rhythms produced by the
brain and heart and that human autonomic nervous system activity reflected in heart rate …

A new analysis technique for the evaluation of the degree of synchronization between the
physiological state of a group of people and changes in the Earth's magnetic field based on …

Classification is an important data mining task that widely used in several different real world
applications. In microarray analysis, classification techniques are applied in order to …

Time series forecasting by fuzzy inference systems based on optimal non-uniform attractor
embedding in the multidimensional delay phase space is analyzed in this paper. A near …

In recent years, emotional neural networks (ENNs) have been extensively used in the field of
time series prediction. As a variant of ENN, the radial basis emotional neural network …

The optimal selection of parameters for time-delay embedding is crucial to the analysis and
the forecasting of chaotic time series. Although various parameter selection techniques have …