abstract the aim of this article is to study the function of khoy as a medium sized city in the spatial development of the azerbaijan gharbi province. the research method is descriptive – analytical. the quantative models have been used to study the place of the city and it's hinterland. the population models indicate that the khoy city has the capacity to attract emigrants. if it is not c...

In this work, an artificial neural network (ANN) model along with a combination of adaptive neuro-fuzzy inference system (ANFIS) and particle swarm optimization (PSO) i.e. (PSO-ANFIS) are proposed for modeling and prediction of the propylene/propane adsorption under various conditions. Using these computational intelligence (CI) approaches, the input parameters such as adsorbent shape (S<su...

In the present study, two different data-driven models, artificial neural network (ANN) and multiple linear regression (MLR) models, have been developed to predict the 28 days compressive strength of concrete. Seven different parameters namely 3/4 mm sand, 3/8 mm sand, cement content, gravel, maximums size of aggregate, fineness modulus, and water-cement ratio were considered as input variables...

nowadays, due to increasing the complexity of ic engines, calibration task becomes more severe and the need to use surrogate models for investigating of the engine behavior arises. accordingly, many black box modeling approaches have been used in this context among which network based models are of the most powerful approaches thanks to their flexible structures. in this paper four network base...

probabilistic approach of traffic assignment has been primarily developed to provide a more realistic and flexible theoretical framework to represent traveler’s route choice behavior in a transportation network. the problem of path overlapping in network modelling has been one of the main issues to be tackled. due to its flexible covariance structure, probit model can adequately address the pro...

In this paper, we intend to focus on the sensor network applications in firefighting. A distributed algorithm is developed for the sensor network to guide firefighters through a burning area. The sensor network models the danger of the area under coverage as obstacles, and has the property to adapt itself against possible changes. The protocol developed, will integrate the artificial potential ...

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-lineari...