Showing papers by "Azerbaijan State Oil Academy published in 2019"

An artificial neural network model to predict the thermal properties of concrete using different neurons and activation functions

Abstract: Growing concerns on energy consumption of buildings by heating and cooling applications have led to a demand for improved insulating performances of building materials. The establishment of thermal property for a building structure is the key performance indicator for energy efficiency, whereas high accuracy and precision tests are required for its determination which increases time and experimental costs. The main scope of this study is to develop a model based on artificial neural network (ANN) in order to predict the thermal properties of concrete through its mechanical characteristics. Initially, different concrete samples were prepared, and their both mechanical and thermal properties were tested in accordance with ASTM and EN standards. Then, the Levenberg–Marquardt algorithm was used for training the neural network in the single hidden layer using 5, 10, 15, 20, and 25 neurons, respectively. For each thermal property, various activation functions such as tangent sigmoid functions and triangular basis functions were used to examine the best solution performance. Moreover, a cross-validation technique was used to ensure good generalization and to avoid overtraining. ANN results showed that the best overall R2 performances for the prediction of thermal conductivity, specific heat, and thermal diffusivity were obtained as 0.996, 0.983, and 0.995 for tansig activation functions with 25, 25, and 20 neurons, respectively. The performance results showed that there was a great consistency between the predicted and tested results, demonstrating the feasibility and practicability of the proposed ANN models for predicting the thermal property of a concrete.

Technology for Combined Desalination of Sea Water

Abstract: The expediency of mastering the systems for combined desalination of sea water based on the reverse osmosis method and thermal distillation method using the exhaust heat of power plants has been substantiated. The technology of Mg-Na-cation-exchange decalcification is proposed for preventing the sulfate scale formation. This technology provides for the regeneration of cation-exchange resin by the mixture of magnesium and sodium salts contained in the purge solution at the stage of thermal distillation of reverse osmosis concentrate. It has been shown that the conversion of the softened Caspian and Black Sea waters by using the combined desalination can be raised to the levels of 87.4 and 81.9%, respectively. The performed investigations were of the computational and analytical character.

Parallel solution of features subset selection process for hand-printed character recognition

Abstract: *Correspondence: Elviz Ismayilov Azerbaijan State Oil and Industry University, Baku, Azerbaijan, elviz. ismayilov@gmail.com, Abstract The existence of a huge amount of features for pattern recognition problems brings to the overloading of the training and exploitation steps of the recognition; also, highly correlated features affect the accuracy of the designed systems negatively. One of the most used ways for tackling this problem is the application of genetic algorithms for the solution of the binary optimization problems that appeared during the features subset selection process. In this paper was used parallel genetic algorithms for the selection of the most informative features in Azerbaijani hand-printed character recognition system by using opportunities of the distributed cluster computing. In this way after the given number of generations most appropriate features with the high recognition rate were selected from the features database.

Multiattribute Evaluation of Weapon Systems Under Z-Information

Abstract: Weapon systems are complex technical systems characterized by imperfect relevant information. Zadeh introduced the Z-number concept to formalize imprecision and partial reliability of information. In this paper, we consider a hierarchical decision making based on an evaluation of weapon systems under Z-number-based information. Z-number-valued weighted average aggregation operator is used for solving of this problem.