in the present study, computational fluid dynamics (cfd) techniques and artificial neural networks (ann) are used to predict the pressure drop value (δp ) of al2o3-water nanofluid in flat tubes. δp  is predicted taking into account five input variables: tube flattening (h), inlet volumetric flow rate (qi  ), wall heat flux (qnw  ), nanoparticle volume fraction (φ) and nanoparticle diameter (dp ...

because of high cost of drilling and analysis of samples, it needs to predict gold and silvers based on pathfinder such as as, sb, cd, pb and zn and decrease the cost and time exploration project implementation. in this paper, the model based on a multilayer perceptron artificial neural network (mlp-ann) optimized by invasive weed optimization algorithm (iwo) to predict of gold and silver in za...

in this work, artificial neural network (ann) was utilized to develop a new model for the predictionof the kinematic viscosity of petroleum fractions. this model was generated as a function oftemperature (t), normal boiling point temperature (tb), and specific gravity (s). in order to developthe new model, different architectures of feed-forward type were examined. finally, the optimumstructure...

Today self-organization and automatic usage of Artificial Neural Networks (ANN) are common in various applications for financial services providers. We analyze typical advantages and disadvantages of ANN and discuss the question: For which tasks ANN applications are most promising? We show that Intelligent Decision Support Systems (IDSS) based on ANN and Neurosimulators can support today’s comp...

allocation and removing of excess water from the irrigation and drainage network is one of the most important activities in the management of these networks. side weir is one of the most common structures for this purpose. study on the flow hydraulic characteristics of this structure included two parts, defining the water surface profiles and estimating the discharge coefficient. to estimate th...

The aim of this research was to compare the data analytic applicability of a backpropagated neural network with that of regression analysis. Thirty individuals between the ages of 64 and 86 (Mean age = 73.6; Mean years education = 15.4; % women = 50) participated in a study designed to validate a new test of spatial ability administered in virtual reality. As part of this project a standard neu...

This publication by Falola and Genova seeks to serve as an introduction to the global oil industry by highlighting the important aspects of the industry, and the countries, companies and people who influence oil developments. Three arguments run throughout the book, namely that oil is a complex international issue, the intricate connection between oil and politics, and that oil has brought a mi...

We review the structure of cerebral cortex to find out the number of neurons and synapses and its modular structure. The organization of these neurons is then studied and mapped onto the framework of an artificial neural network (ANN). The computational requirements to run this ANN model are then estimated. The conclusion is that it is possible to simulate the mouse cortex today on a cluster co...

Model checking often faces the problem of reducing the large exponential sizes of state-space representations. Several reduction techniques such as bisimulation equivalence, partial-order semantics, and symmetry-based reduction have been proposed, but existing tools do not completely allow a user the flexibility in manipulating state spaces. We propose a new userfriendly verification environmen...