درخت حوزه‌های تخصصی

Passive Defense is a set of civilian efforts performed to enhance deterrence, reduce vulnerability, sustain essential activities, promote national stability, and facilitate crisis management against military threats of an enemy. Since in battles, sensitive and critical areas of cities are of paramount importance,it is clear that in military agressions, a large part of threats are focused on cities and their urban facilities and equipment, especially fuel centers. As a result, consideration of passive defense while planning cities has a significant role in reducing the vulnerability of cities and their urban elements as well as facilitating the urban crisis management. It also provides the citizens resistance threshold under possible enemy invasion and natural malicious agents. Hence, this article reviews and analyzes the current situation of gas distribution centers and evaluates their positioning across the city of Mashhad with regard to passive defense approach. However, as far as there is no clear- cut criteria for organizing fuel centers with passive defense approach, the Delphi method is used to select the desired criteria in which on the basis of the final comments of the experts, four critera- performance, access, hazards and security election and spatial organization of the fuel tanks and petrol stations- are analyzed using AHP model and GIS spatial analyzes. Accordingly, it can be said that the assessment of the current status of the urban fuel stations in Mashhad indicates that no area of the city enjoys all measures of passive defense (performance, availability, security, and risks). Likewise, the results indicate that the distribution of these centers in the city are mostly consistent with the factor of access. taking into account all the criteria, it is the ​​North West of Mashhad which has the highest utility than other areas. It is followed by the east of Mashhad and ​​the Northeast and the middle east of the city, respectively. Accordingly, it could be stated that ignoring an efficient design for determining the optimum location of the site construction with a passive defense approach results in an inappropriate and naive spatial distribution of the stations leading to an increased security and environmental risks of the city.

No unique method has been so far specified for determining the number of neurons in hidden layers of Multi-Layer Perceptron (MLP) neural networks used for prediction. The present research is intended to optimize the number of neurons using two meta-heuristic procedures namely genetic and hill climbing algorithms. The data used in the present research for prediction are consumption data of water subscribers in Fasa City of Fars Province (Iran) between the years 2010 to 2013. Ultimately, using the respective data set, the data of the subsequent year 2014 can be predicted. In the present research it was observed that the mean square errors of per data (MSEPD) for the abovementioned algorithms are less than 0.2, indicating a high performance in the neural networks’ prediction. Correlation coefficients using genetic and hill climbing algorithms were respectively equal to 0.891 and 0.759. Thus, GA was able to leave a better effect on optimization of neural network.