Gas Analysis System Based on Artificial Neural Networks

Distillation Column Identification Using Artificial Neural Network

  Abstract: In this paper, Artificial Neural Network (ANN) was used for modeling the nonlinear structure of a debutanizer column in a refinery gas process plant. The actual input-output data of the system were measured in order to be used for system identification based on root mean square error (RMSE) minimization approach. It was shown that the designed recurrent neural network is able to pr...

Forecasting Energy Price and Consumption for Iranian Industrial Sectors Using ANN and ANFIS

Forecasting energy price and consumption is essential in making effective managerial decisions and plans. While there are many sophisticated mathematical methods developed so far to forecast, some nature-based intelligent algorithms with desired characteristics have been developed recently. The main objective of this research is short term forecasting of energy price and consumption in Iranian ...

Prediction of Gas Lift Parameters Using Artificial Neural Networks

Yarn tenacity modeling using artificial neural networks and development of a decision support system based on genetic algorithms

Yarn tenacity is one of the most important properties in yarn production. This paper addresses modeling of yarn tenacity as well as optimally determining the amounts of the effective inputs to produce yarn with desired tenacity. The artificial neural network is used as a suitable structure for tenacity modeling of cotton yarn with 30 Ne. As the first step for modeling, the empirical data is col...

On the convergence speed of artificial neural networks in‎ ‎the solving of linear ‎systems

‎Artificial neural networks have the advantages such as learning, ‎adaptation‎, ‎fault-tolerance‎, ‎parallelism and generalization‎. ‎This ‎paper is a scrutiny on the application of diverse learning methods‎ ‎in speed of convergence in neural networks‎. ‎For this aim‎, ‎first we ‎introduce a perceptron method based on artificial neural networks‎ ‎which has been applied for solving a non-singula...

Optimum Design of Liquified Natural Gas Bi-lobe Tanks using Finite Element, Genetic Algorithm and Neural Network

A comprehensive set of ten artificial neural networks is developed to suggest optimal dimensions of type ‘C’ Bi-lobe tanks used in the shipping of liquefied natural gas. Multi-objective optimization technique considering the maximum capacity and minimum cost of vessels are implemented for determining optimum vessel dimensions. Generated populations from a genet...