Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden nodes, IEEE Trans. Neural Networks 17(4) (2006) 879–892] has recently proposed an incremental extreme learning machine (I-ELM), which randomly adds hidden nodes incrementally and analytically determines the output weights. Although hidden nodes are generated randomly, the network constru...

Table 1: Phoneme recognition rates for diierent hybrid RBF-HMM systems; all values in %. In line two the results for a NN with one additional hidden layer of 100 sigmoidal units are depicted. The recognition rates for both training procedures are inferior to the net without hidden layer. This is mainly contributed to the relatively small hidden layer with 100 nodes, which acts like a bottleneck...

Error Minimized Extreme Learning Machine (EM-ELM) proposed by Feng et al. [1] can automatically determine the number of hidden nodes in generalized Single-hidden Layer Feedforward Networks (SLFNs). We recently found that some of the hidden nodes that are added into the network may play a very minor role in the network output, which increases the network complexity. Hence, this paper proposes an...

To estimate the Cation Exchange Capacity (CEC), indirect manner used of Pedotransfer Functions (PTFs). CEC is one of the important soil fertility factors, and not measured directly because it is costly and time consuming. Thus, used from regression equations between easily and non-easily soil properties. The purpose of this research, is develop the PTFs for CEC, with use of easily available soi...

Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden nodes, IEEE Transactions on Neural Networks 17(4) (2006) 879–892] have recently proposed a new theory to show that single-hidden-layer feedforward networks (SLFNs) with randomly generated additive or radial basis functi...

A virtual chemical spectrophotometer for the simultaneous analysis of nickel (Ni) and cobalt (Co) was developed based on an artificial neural network (ANN). The developed ANN correlates the respective concentrations of Co and Ni given the absorbance profile of a Co-Ni mixture based on the BeerâĂŹs Law. The virtual chemical spectrometer was trained using a 3-layer jump connection neural network ...

223 Abstract— Data mining techniques are broadly classified into two classes (i) Statistical Techniques and (ii) Knowledge Discovery. The continuing rapid growth of on-line data and the widespread use of databases necessitate the development of techniques for extracting useful knowledge and for facilitating database access. This paper analyzes the results of multilayer perceptron with pace regr...

In this study, we propose a novel learning approach of Radial Basis Function Neural Network (RBFNN) based on Fuzzy C-Means (FCM) and Quantum Particle Swarm Optimization (QPSO) to group similar data. The performance of RBFNN relies on the parameters such as number of hidden nodes, centres and width of Gaussian function and weight matrix between hidden layer and output layer. Generally, RBF is tr...