The forecast of fluctuations and prices is the major concern in financial markets. Thus, developing an accurate and robust forecasting decision model is critically favorable to the investors. As gold has shown a special capability to smooth inflation fluctuations, governors use gold as a price controlling lever. Thus, more information about future gold price trends will help to make the firm de...

Radial Basis Function Neural Networks (RBF NNs) are one of the most applicable NNs in the classification of real targets. Despite the use of recursive methods and gradient descent for training RBF NNs, classification improper accuracy, failing to local minimum and low-convergence speed are defects of this type of network. In order to overcome these defects, heuristic and meta-heuristic algorith...

Neural Networks have become very useful tools for input-output knowledge discovery. However, some of the most powerful schemes require very complex machines, and thus a large amount of calculation. This paper presents a general technique to reduce the computational burden associated to the operational phase of most neural networks that calculate their output as a weighted sum of terms, which co...

a neural network is developed for the determination of leaky confined aquifer parameters. leakage into the aquifer takes place from the storage in the confining aquitard. the network is trained for the well function of leaky confined aquifers by the back propagation technique and adopting the levenberg–marquardt optimization algorithm. by applying the principal component analysis (pca) on the a...

This paper introduces a novel method for human face recognition that employs a set of different kind of features from the face images with Radial Basis Function (RBF) neural network called the Hybrid N-Feature Neural Network (HNFNN) human face recognition system. The face image is projected in each appropriately selected transform methods in parallel. The output of the RBF classifiers are fused...

Query expansion methods have been extensively studied in information retrieval. This paper proposes a query expansion method. The HQE method employs a combination of ontology-based collaborative filtering and neural networks to improve query expansion. In the HQE method, ontology-based collaborative filtering is used to analyze semantic relationships in order to find the similar users, and the ...

This paper presents a set of optimizations in learning algorithms commonly used for training radial basis function neural networks. These optimizations are applied to a RBF neural network used in identifying helicopter types processing their rotor sounds. The first method uses an optimum learning rate in each iteration of train process. This method increases the speed of learning process and al...

This paper presents a novel algorithm that modifies the speech uttered by a source speaker to sound as if produced by a target speaker. In particular, we address the issue of transformation of the vocal tract characteristics from one speaker to another. The approach is based on estimating spectral envelopes using radial basis function (RBF) networks, which is one of the well-known models of art...

Forecasting the unit cost of a semiconductor product is an important task to the manufacturer. However, it is not easy to deal with the uncertainty in the unit cost. In order to effectively forecast the semiconductor unit cost, a collaborative and artificial intelligence approach is proposed in this study. In the proposed methodology, a group of domain experts is formed. These domain experts ar...