The use of statistical data and of the neural networks, capable of elaborate a series of data and territorial info, have allowed the making of a model useful in the subdivision of urban places into homogeneous zone under the profile of a social, real estate, environmental and urbanist background of a city. The development of homogeneous zone has fiscal and urbanist advantages. The tools in the ...

After extreme events such as floods, thunderstorms, blizzards and hurricanes there will be devastating effects in the distribution networks which may cause a partial or complete blackout. Then, the major concern for the system operators is to restore the maximum critical loads as soon as possible by available generation units.  In order to solve this problem, this paper provides a restoration s...

Considering the network structure is one of the new approaches in studying stochastic PERT networks (SPN). In this paper, planar networks are studied as a special class of networks. Two structural reducible mechanisms titled arc contraction and deletion are developed to convert any planar network to a series-parallel network structure. In series-parallel SPN, the completion time distribution f...

Generative adversarial networks (GANs) [7] are a recent approach to train generative models of data, which have been shown to work particularly well on image data. In the current paper we introduce a new model for texture synthesis based on GAN learning. By extending the input noise distribution space from a single vector to a whole spatial tensor, we create an architecture with properties well...

a methodology is presented in this paper to find optimal location and dosage of chlorine injection in water distribution networks. the objective is to minimize the chlorine consumption while keeping the residual chlorine at each node within the standard range. unfortunately because of wrong water quality management in water distribution networks in many parts of the world, many problems such...

One of the big concerns of big cities is facing with the increase of fossil fuel vehicles in the roads. The cars intensify greenhouse gas emission in civic centers. One approach to reduce the emission is replacing the cars by Plug-In Electric Vehicles (PEVs). In spite of reducing the emission, PEVs have some adverse effect on electric distribution networks. Technical challenges such as load and...

We study the impact on productivity of specific operating practices currently used by demand responsive transit (DRT) providers. We investigate the effect of using a zoning vs. a no-zoning strategy and time-window settings on performance measures such as total trip miles, deadhead miles and fleet size. It is difficult to establish closed form expressions to assess the impact on the performance ...

We present a new approach for the empirical investigation of agglomeration patterns. We examine the clustering of manufacturing firms by identifying patterns of spatial network formation that deviate from randomly generated networks. Using firm-level panel data from Vietnam we calculate transitivity, a measure to determine the strength of clustering of manufacturing firms. We then test whether ...

This paper describes a geometry based technique for feature extraction applicable to segmentation-based word recognition systems. The proposed system extracts the geometric features of the character contour. This features are based on the basic line types that forms the character skeleton. The system gives a feature vector as its output. The feature vectors so generated from a training set, wer...

When artifical neural networks (ANN) are used in the prediction problems, it is usually desirable that some form of confidence bound is placed on the predicted value. Methods to estimate the confidence bound are available. However, these methods are valid under certain assumptions, which are rarely satisfied in practice. The behavior of the estimated confidence bound are not well understood whe...