one of the most important problems in the system reliability optimization is redundancy allocation problem that has been studied in different system configurations. k-out-of-n structure is a general system configuration and offers enhanced capabilities for analyzing more design problems. hence, in this paper, the redundancy allocation problem of k-out-of-n systems is studied. in the most previo...

The hydraulic and thermal simulation of crude oil pipeline transportation is greatly significant for the safe accurate regulation pipelines. With reasonable basic parameters, solution traditional partial differential equation (PDE) axial soil temperature field on can obtain results, yet it brings about a low calculation efficiency problem. In order to overcome low-efficiency problem, an efficie...

Deep-unfolding neural networks (NNs) have received great attention since they achieve satisfactory performance with relatively low complexity. Typically, these deep-unfolding NNs are restricted to a fixed-depth for all inputs. However, the optimal number of layers required convergence changes different In this paper, we first develop framework deep deterministic policy gradient (DDPG)-driven ad...

The problem of optimal economic operation of hydrothermal electric power systems is solved using powerful continuation method. While in conventional approach, fixed generation voltages are used to avoid convergence problems, in the proposed algorithm, they are treated as variables so that better solutions can be obtained. The algorithm is tested for a typical 5-bus and 17-bus New Zealand networ...

In this paper, using the three-phase induction motor fifth order model in a stationary twoaxis reference frame with stator current and rotor flux as state variables, a conventional backsteppingcontroller is first designed for speed and rotor flux control of an induction motor drive. Then in orderto make the control system stable and robust against all electromechanical parameter uncertainties a...

In this article, the multi-objective optimization of cylindrical aluminum tubes under axial impact load is presented.The absorbed energy and the specific absorbed energy (SEA) are considered as objective functions while the maximum crush load should not exceed allowable limit. The geometric dimensions of tubes including diameter, length and thickness are chosen as design variables. The Non-domi...

neural networks are applicable in identification systems from input-output data. in this report, we analyze thehammerstein-wiener models and identify them. thehammerstein-wiener systems are the simplest type of block orientednonlinear systems where the linear dynamic block issandwiched in between two static nonlinear blocks, whichappear in many engineering applications; the aim of nonlinearsyst...

In this study, polynomial-based radial basis function neural networks are proposed as one of the functional components of the overall face recognition system. The system consists of the preprocessing and recognition module. The design methodology and resulting procedure of the proposed P-RBF NNs are presented. The structure helps construct a solution to high-dimensional pattern recognition prob...