forecasting of temperature is a very important in meteorology. air temperature prediction is of a concern in environment, industry and agriculture. temperature with precipitation are important factors in meteorology and are used in classification of climate. in this paper we want to predict average monthly temperature for chosen station of isfahan province. an artificial neural network is a pow...

in this study, a three–layer artificial neural network (ann) model was developed to predict the pressure gradient in horizontal liquid–liquid separated flow. a total of 455 data points were collected from 13 data sources to develop the ann model. superficial velocities, viscosity ratio and density ratio of oil to water, and roughness and inner diameter of pipe were used as input parameters of t...

static deformation modulus is recognized as one of the most important parameters governing the behavior of rock masses. predictive models for the mechanical properties of rock masses have been used in rock engineering because direct measurement of the properties is difficult due to time and cost constraints. in this method the deformation modulus is estimated indirectly from classification syst...

It is widely believed in the pattern recognition field that the number of examples needed to achieve an acceptable level of generalization ability depends on the number of independent parameters needed to specify the network configuration. The paper presents a neural network for classification of high-dimensional patterns. The network architecture proposed here uses a layer which extracts the g...

Constrained optimization problems have a wide range of applications in science, economics, and engineering. In this paper, a neural network model is proposed to solve a class of nonsmooth constrained optimization problems with a nonsmooth convex objective function subject to nonlinear inequality and affine equality constraints. It is a one-layer non-penalty recurrent neural network based on the...

abstract erosion and sedimentation are the most complicated problems in hydrodynamic which are very important in water-related projects of arid and semi-arid basins. for this reason, the presence of suitable methods for good estimation of suspended sediment load of rivers is very valuable. solving hydrodynamic equations related to these phenomenons and access to a mathematical-conceptual model ...

We investigate a minimalistic abstraction for a multi-layer spiking neural network (SNN), in order to gain fundamental insight into classifying spatiotemporal patterns using temporal coding. The firing model is based on coincidence detection with temporal binning: a neuron X fires at time t if at least η > 1 upstream neurons fire prior to t such that the spikes arrive at X in an interval [t−δ/2...

in this paper, a fault diagnosis system based on discrete wavelet transform (dwt) and artificial neural networks (anns) is designed to diagnose different types of fault in gears. dwt is an advanced signal-processing technique for fault detection and identification. five features of wavelet transform rms, crest factor, kurtosis, standard deviation and skewness of discrete wavelet coefficients of...