The types of traditional houses vary from region to region according to physical and non-physical circumstances, and Sulaymaniyah city is characterized by a type of traditional houses that differ significantly from those in most cities and regions neighboring are always different from the general pattern that is prevalent in the region and the Muslim world.

The aim of this research is to study the cause of this difference or distinction in the traditional houses in Sulaimaniyah city, by comparing the most common models in these houses and comparing them with the general models of village houses that originally existed in the region to relaize the convergence and contrast between them. The research was based on a co

     In this paper, the propose is to use the xtreme value distribution as the rate of occurrence of the non-homogenous Poisson process, in order to improve the rate of occurrence of the non-homogenous process, which has been called the Extreme value Process. To estimate the parameters of this process, it is proposed to use the Maximum Likelihood method, Method of Moment and a smart method represented by the Artificial Bee Colony:(ABC) algorithm to reach an estimator for this process which represents the best data representation. The results of the three methods are compared through a simulation of the model, and it is concluded that the estimator of (ABC) is better than the estimator of the maximum likelihood method and method of mo

The possibility of implementing smart mobility in the traditional city: Studying the possibility of establishing an intelligent transportation system in the city center of Kadhimiya

The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed