The generalized Brain-State-in-a-Box (gBSB) neural network is a generalized version of the BrainState-in-a-Box (BSB) neural network. The BSB net is a simple nonlinear autoassociative neural network that was proposed by J. A. Anderson, J. W. Silverstein, S. A. Ritz, and R. S. Jones in 1977 as a memory model based on neurophysiological considerations. The BSB model gets its name from the fact tha...

Artificial Neural Network has been popularly used for forecasting purposes over the past. There are some innate problems in neural network such as indefinite configuration, architecture, and learning issues, etc. To vanquish these problems, Generalized Neural Network (GNN) has been used. This paper illustrates the development of Quantum GA-GNN method for forecasting of solar photovoltaic system...

the application of neural networks to model a laboratory scale inverse fluidized bed reactor has been studied. a radial basis function neural network has been successfully employed for the modeling of the inverse fluidized bed reactor. in the proposed model, the trained neural network represents the kinetics of biological decomposition of organic matters in the reactor. the neural network has b...

in this paper, a novel hybrid model based on neural network and game theory is proposed to support the analyzers in oil market. in this model, first the neural network is utilized to learn the oil prices associated with opec production level and usa imports level. then the learned neural network is applied by a game model. finally the nash equilibrium points of the game present the optimum deci...

This paper examines the generalization capability in learning multiple temporal patterns by the recurrent neural network with parametric bias (RNNPB). Our simulation experiments indicated that the RNNPB can learn multiple patterns as generalized by extracting relational structures shared among the training patterns. It was, however, shown that such generalizations cannot be achieved when the re...

For more than a decade, prediction error has been one powerful tool to measure the performance of a neural network. In this paper, we extend the technique to a kind of fault tolerant neural network. Consider a neural network to be suffering from multiple-node fault, a formulae similar to that of Generalized Prediction Error has been derived. Hence, the effective number of parameter of such a fa...

Software development effort prediction is one of the most key activities in software industry. Many models have been proposed to build a relationship between software size and effort; however we still have problems for effort prediction. This is because project data, available in the primary stages of project is often inadequate, unpredictable, uncertain and unclear. The need for accurate effor...

Punching shear capacity is a key factor for governing the collapsed form of slabs. This fragile failure that occurs at the slab-column connection is called punching shear failure and has been of concern for the engineers. The most common practice in evaluating the punching strength of the concrete slabs is to use the empirical expressions available in different building design codes. The estima...