the quality of wastewater generated in any process industry is generally indicated by performance indices namely bod, cod and toc, expressed in mg/l. the use of toc as an analytica parameter has become more common in recent years especially for the treatment of industrial wastewater. in this study, several empirical relationships were established between bod and cod with toc using regression an...

a back propagation artificial neural network (bpann) is a well-known learning algorithmpredicated on a gradient descent method that minimizes the square error involving the networkoutput and the goal of output values. in this study, 261 gps/leveling and 8869 gravity intensityvalues of iran were selected, then the geoid with three methods “ellipsoidal stokes integral”,“bpann”, and “collocation” ...

this paper deals with leader-following and leaderless consensus problems of high-order multi-input/multi-output (mimo) multi-agent systems with unknown nonlinear dynamics in the presence of uncertain external disturbances. the agents may have different dynamics and communicate together under a directed graph. a distributed adaptive method is designed for both cases. the structures of the contro...

no unique method has been so far specified for determining the number of neurons in hidden layers of multi-layer perceptron (mlp) neural networks used for prediction. the present research is intended to optimize the number of neurons using two meta-heuristic procedures namely genetic and hill climbing algorithms. the data used in the present research for prediction are consumption data of water...

The current study proposes a two-step approach for pore facies characterization in the carbonate reservoirs with an example from the Kangan and Dalanformations in the South Pars gas field. In the first step, pore facies were determined based on Mercury Injection Capillary Pressure (MICP) data incorporation with the Hierarchical Clustering Analysis (HCA) method. In the next step, polynomial meta...

This paper intends to offer a new iterative method based on articial neural networks for finding solution of a fuzzy equations system. Our proposed fuzzied neural network is a ve-layer feedback neural network that corresponding connection weights to output layer are fuzzy numbers. This architecture of articial neural networks, can get a real input vector and calculates its corresponding fuzzy o...