Reservoir characterization and asset management require comprehensive information about formation fluids. In fact, it is not possible to find accurate solutions to many petroleum engineering problems without having accurate pressure-volume-temperature (PVT) data. Traditionally, fluid information has been obtained by capturing samples and then by measuring the PVT properties in a laboratory. In ...

estimation of pure runoff is a house virtually is complex and different methods of calculation have been proposed. modern methods of solving problems in river engineering and water homes and assess the flow method is used, is that the artificial network pattern of human brain neural network training process, while implementation of the internal relationships between the data and discover for ot...

Production of highly viscous tar sand bitumen using Steam Assisted Gravity Drainage (SAGD) with a pair of horizontal wells has advantages over conventional steam flooding. This paper explores the use of Artificial Neural Networks (ANNs) as an alternative to the traditional SAGD simulation approach. Feed forward, multi-layered neural network meta-models are trained through the Back-Error-Propaga...

Handwriting recognition has been one of the active and challenging research areas in the field of image processing and pattern recognition. It has numerous applications that includes, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. Neural Network (NN) with its inherent learning ability offers promising solutions for handwritten characte...

This paper presents a Hammerstein-Wiener recurrent neural network (HWRNN) with a systematic identification algorithm for identifying unknown dynamic nonlinear systems. The proposed HWRNN resembles the conventional Hammerstein-Wiener model that consists of a linear dynamic subsystem that is sandwiched in between two nonlinear static subsystems. The static nonlinear parts are constituted by feedf...

This paper presents Artificial Neural Network (ANN) implementation for Mechanical modeling of Radio Frequency Micro Electro Mechanical System (RF MEMS) lateral double beam switch. We propose an efficient approach based on ANN for analyzing the static and dynamic characteristics of RF MEMS lateral switch by calculating its characteristics parameters. ANN model were trained with five learning alg...

this paper presents a new model for predicting the compressive strength of steel-confined concrete on circular concrete filled steel tube (ccfst) stub columns under axial loading condition based on artificial neural networks (anns) by using a large wide of experimental investigations. the input parameters were selected based on past studies such as outer diameter of column, compressive strength...

abstract background: a computer aided diagnosis system was established using the wavelet transform and neural network to differentiate malignant from benign in a   group of patients with histo-pathologically proved breast lesions based on the data derived independ­ently from time-intensity profile.   materials and methods: the per­formance of the artificial neural network (ann) was evaluated us...

introduction: intravenous general anesthetic agents are among the most important and widely used anesthetic drugs in the clinical practice. many pharmacological studies have shown that potentiation of gaba and glycine on their receptors is the most plausible mechanism. nevertheless, there is limited information on the effects of co-administration of two or more of these agents. however, experim...