Analysis on Network Model Parameters of BP Neural Network in the Assessment for Bridge Reliability

title: A Study on the Application of GA-BP Neural Network in the Bridge Reliability Assessment

title: WiMAX Overview and System Performance
abstract: In this paper, the performance of WiMax network with DL SIMO, DL MIMO and UL SIMO is analyzed via system simulations. Two data traffic models are considered, namely Web browsing (HTTP) and full buffer sessions, operating in multi path fading channels such as the ITU pedestrian-B and vehicular-A channels. The control channel coverage and reliability of WiMAX using realistic overhead is also analyzed in this paper.

title: Modeling of power electronics for simulation based analysis of power systems
abstract: Given the increased penetration of power electronic converters in power systems it is necessary to study their impact in the system operation. In order to achieve that goal the power converters must be appropriately modeled in simulation or analytical studies. This paper reviews the modeling requirements and characteristics of power electronic converter models for system studies. Several models of the equipment used in a ship power system are described. The use of these models in simulation based system studies is discussed in the paper. Stability analysis is used as example for that discussion. The models are grouped into categories based on their degree of detail and use. Moreover, the validity and computational requirements of those models are also discussed.

title: A stochastic beam search for the berth allocation problem
abstract: In this paper, the optimization of the Berth Allocation Problem (BAP) is transformed into a multiple stage decision making procedure and a new multiple stage search method, namely stochastic beam search algorithm, is proposed to solve it. New techniques such as an improved beam search scheme, a two-phase node goodness estimation, and a stochastic node selection criteria are proposed. Real-life information provided by Singapore Port was collected as our test data. Experimental results show that the proposed stochastic beam search is more accurate and efficient than both the state-of-the-art meta-heuristic and the traditional determinist beam search.

title: Even aberration measurement of lithographic projection system based on optimized phase-shifting marks
abstract: In the present paper, we propose a novel method for measuring the even aberrations of lithographic projection optics by use of optimized phase-shifting marks on the test mask. The line/space ratio of the phase-shifting marks is optimized to obtain the maximum sensitivities of Zernike coefficients corresponding to even aberrations. Spherical aberration and astigmatism can be calculated from the focus shifts of phase-shifting gratings oriented at 0^o, 45^o, 90^o and 135^o at multiple illumination settings. The PROLITH simulation results show that, the measurement accuracy of spherical aberration and astigmatism obviously increase, after the optimization of the measurement mark.

title: Short-Term Traffic Flow Prediction Based on Parallel Quasi-Newton Neural Network
abstract: Identifying and predicting the situation of traffic flow play an important role in traveler information broadcast and real-time traffic control. In this paper, a short-term traffic flow prediction model based on the parallel self-scaling quasi-Newton (SSPQN) neural network is presented. In this method, a set of parallel search directions are generated at the beginning of each iteration. Each of these directions is selectively chosen from a representative class of quasi-Newton (QN) methods. Inexact line searches are then carried out to estimate the minimum point along each search direction. Experimental and analytical results demonstrate the feasibility of applying SSPQN to traffic flow prediction and prove that it can better satisfy real-time demand of traffic flow prediction.