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Neural Network-based Constant Current Control of Dynamic Wireless Power Supply System for Electric Vehicles  [PDF]
Yong Tian,Yue Sun,Yugang Su,Zhihui Wang
Information Technology Journal , 2012,
Abstract: In the dynamic wireless power supply system for electric vehicles, the output current is influenced by factors, including primary rail current, relative position between pick-up unit and track, capacity of battery packs. Negative effect of those factors may lead to unsteady output. Aimed at the question of accurately modeling and output control caused by higher-order switch nonlinear behavior and multi-disturbance factor. An output current-stabilizing control strategy based on back-propagation (BP) neural network is proposed, making heavy use of nonlinear function approximation character and powerful generalization capability for neural network. With this strategy, the system was robust enough to unknown disturbance and parameter variation and output current can keep constant unswervingly. Finally, simulation results show that this control strategy has obvious advantages both in overshoot and setting time over conventional PID control method.
Modeling Transportation Routines using Hybrid Dynamic Mixed Networks  [PDF]
Vibhav Gogate,Rina Dechter,Bozhena Bidyuk,Craig Rindt,James Marca
Computer Science , 2012,
Abstract: This paper describes a general framework called Hybrid Dynamic Mixed Networks (HDMNs) which are Hybrid Dynamic Bayesian Networks that allow representation of discrete deterministic information in the form of constraints. We propose approximate inference algorithms that integrate and adjust well known algorithmic principles such as Generalized Belief Propagation, Rao-Blackwellised Particle Filtering and Constraint Propagation to address the complexity of modeling and reasoning in HDMNs. We use this framework to model a person's travel activity over time and to predict destination and routes given the current location. We present a preliminary empirical evaluation demonstrating the effectiveness of our modeling framework and algorithms using several variants of the activity model.
Complexity Perspectives on Transportation Network
交通运输网络的复杂性研究

MO Huihui,WANG Jiao''e,JIN Fengjun,
莫辉辉
,王姣娥,金凤君

地理科学进展 , 2008,
Abstract: Based on analyzing complex network theory applied in aviation,railway and urban transportation,we conclude that complexity of transportation network comes from its systematic complexity,and that the general analysis method of complex network ignores the attribute of geo-graphic space,which brings out many problems in analyzing real-world network.Complex network analysis based on statistical physics is mostly about theoretical analysis or data modeling on topol-ogy network,which has greater disparity in transportation networks and dynamic mechanism.Transportation network includes four kinds of network structure:demand network,organization network,route network and infrastructure network,and is a compound networked structure with open complex system.Transportation is a kind of science which focuses strongly on practical ap-plication,so it needs a recurrent force to drive theory to modal and method,then to practice.We put forward in future some vital aspects of complexity analysis on transportation network,which includes(1)elemental recognition on the structure complexity of transportation system;(2)network complex analysis based on geographic spatial characteristics;(3)analysis and application of net-work structure based on organization and efficiency;(4)interplay between the network structure and flow caused by interaction;(5)character of local structure of network and its effect on global structure;and(6)network evolution affected by systemic open.
Dynamic Modeling and Simulation of a Switched Reluctance Motor in a Series Hybrid Electric Vehicle
Siavash Sadeghi,Mojtaba Mirsalim,Arash Hassanpour Isfahani
Acta Polytechnica Hungarica , 2010,
Abstract: Dynamic behavior analysis of electric motors is required in order to accuratelyevaluate the performance, energy consumption and pollution level of hybrid electricvehicles. Simulation tools for hybrid electric vehicles are divided into steady state anddynamic models. Tools with steady-state models are useful for system-level analysiswhereas tools that utilize dynamic models give in-depth information about the behavior ofsublevel components. For the accurate prediction of hybrid electric vehicle performance,dynamic modeling of the motor and other components is necessary. Whereas the switchedreluctance machine is well suited for electric and hybrid electric vehicles, due to the simpleand rugged construction, low cost, and ability to operate over a wide speed range atconstant power, in this paper dynamic performance of the switched reluctance motor for eseries hybrid electric vehicles is investigated. For this purpose a switched reluctance motorwith its electrical drive is modeld and simulated first, and then the other components of aseries hybrid electric vehicle, such as battery, generator, internal combusion engine, andgearbox, are designed and linked with the electric motor. Finally a typical series hybridelectric vehicle is simulated for different drive cycles. The extensive simulation results showthe dynamic performance of SRM, battery, fuel consumption, and emissions.
Dynamic Modeling and Simulation on a Hybrid Power System for Electric Vehicle Applications  [PDF]
Hong-Wen He,Rui Xiong,Yu-Hua Chang
Energies , 2010, DOI: 10.3390/en3111821
Abstract: Hybrid power systems, formed by combining high-energy-density batteries and high-power-density ultracapacitors in appropriate ways, provide high-performance and high-efficiency power systems for electric vehicle applications. This paper first establishes dynamic models for the ultracapacitor, the battery and a passive hybrid power system, and then based on the dynamic models a comparative simulation between a battery only power system and the proposed hybrid power system was done under the UDDS (Urban Dynamometer Driving Schedule). The simulation results showed that the hybrid power system could greatly optimize and improve the efficiency of the batteries and their dynamic current was also decreased due to the participation of the ultracapacitors, which would have a good influence on batteries’ cycle life. Finally, the parameter matching for the passive hybrid power system was studied by simulation and comparisons.
Network routing in a dynamic environment  [PDF]
Nozer D. Singpurwalla
Statistics , 2011, DOI: 10.1214/10-AOAS453
Abstract: Recently, there has been an explosion of work on network routing in hostile environments. Hostile environments tend to be dynamic, and the motivation for this work stems from the scenario of IED placements by insurgents in a logistical network. For discussion, we consider here a sub-network abstracted from a real network, and propose a framework for route selection. What distinguishes our work from related work is its decision theoretic foundation, and statistical considerations pertaining to probability assessments. The latter entails the fusion of data from diverse sources, modeling the socio-psychological behavior of adversaries, and likelihood functions that are induced by simulation. This paper demonstrates the role of statistical inference and data analysis on problems that have traditionally belonged in the domain of computer science, communications, transportation science, and operations research.
Travel Itinerary Planning in Public Transportation Network Using Activity-Based Modeling
S. Kolyaie,M.R. Delavar,M.R. Malek
Journal of Applied Sciences , 2009,
Abstract: This study presents a new geospatial information system-based solution that assists people in trip planning to reach multiple destinations considering opening hours of points of interest and duration needed to perform multiple activities using multimodel public transportation media. People encounter with complexities in finding optimum paths in a multimodel public transportation system as they need to consider interactions of different modes of transportations in a more specific and constrained spatio-temporal structure. In this situation people’s context in the form of their activities diary becomes an important issue affecting trip planning and selecting mode of transportation. Activities diary constrains the spatio-temporal order of activities and enables us to study the effect of activities in transportation planning. In this study, the impact of activity diaries and spatio-temporal dimensions of activities in trip planning and optimum path findings are discussed. A new algorithm is proposed for planning itinerary considering network, time and duration constraints. The algorithm assumes that the activities are mandatory and the locations and duration of each activity are fixed. The travelers’ destinations, time and duration constraints provide the input of the algorithm. Using connectivity rules and policies, Dijkstra algorithm for finding the shortest paths is selected. The results determine the possible order of activities and their start and end time. The possible sequences of activities optimized based on minimizing waiting time during the activities i.e., time that person neither is doing an activity nor is traveling between activity locations and must wait till activity can be undertaken according to the time constraints. Finally, efficiency of the algorithm is determined according to the time complexity as a function of number of activity locations in the worst and normal cases. It has been proved that the time complexity of the algorithm depends on the third power of number of activity locations.
Dynamic Web Service Composition based on Network Modeling with Statistical Analysis and Backtracking  [PDF]
M. SureshKumar,P. Varalakshmi
Computer Science , 2012, DOI: 10.5121/ijwsc.2012.3202
Abstract: A Web service is a software system designed to support interoperable machine-to-machine interaction over a network. Web services provide a standard means of interoperating between different software applications, running on a variety of platforms and/or frameworks. One of the main advantages of the usage of web services is its ability to integrate with the other services through web service composition and realize the required functionality. This paper presents a new paradigm of dynamic web services composition using network analysis paired with backtracking. An algorithm called "Zeittafel" for the selection and scheduling of services that are to be composed is also presented. With the proposed system better percentage of job success rate is obtained compared to the existing methodology.
Resuarch of a Dynamic Modeling Method Based on Orthogonal Neural Network
正交神经网络的动态建模方法研究

肖少拥
计算机科学 , 2000,
Abstract: This paper presents a dynamic modeling method based on orthogonal neural network, it fully uses the characteristics of the nonlinear processing ability of neural networks and the efficient disposal of the large scaling sparse problems that Givens transform can process. It can not only train the notwork quickly, but also can optimize the structure of the networks. Simulating experiments show that the new modeling method is a simple universal modeling method for the nonlinear systems.
Neural Network Modeling and System Simulating for the Dynamic Process of Varied Gap Pulsed GTAW with Wire Filler
Guangjun ZHANG,Shanben CHEN,Lin WU,
Guangjun ZHANG
,Shanben CHEN and Lin WU State Key Laboratory of AWPT,Harbin Institute of Technology,Harbin,China Institute of Welding Technology,Shanghai Jiao Tong University,Shanghai,China

材料科学技术学报 , 2005,
Abstract: As the base of the research work on the weld shape control during pulsed gas tungsten arc welding (GTAW) with wire filler, this paper addressed the modeling of the dynamic welding process. Topside length Lt, maximum width Wt and half-length ratio Rh1 were selected to depict topside weld pool shape, and were measured on-line by vision sensing. A dynamic neural network model was constructed to predict the usually unmeasured backside width and topside height of the weld through topside shape parameters and welding parameters. The inputs of the model were the welding parameters (peak current, pulse duty ratio, welding speed, filler rate), the joint gap, the topside pool shape parameters (Lt, Wt, and Rhl), and their history values at two former pulse, a total of 24 numbers. The validating experiment results proved that the artificial neural network (ANN) model had high precision and could be used in process control. At last, with the developed dynamic model, steady and dynamic behavior was analyzed by simulation experiments, which discovered the variation rules of weld pool shape parameters under different welding parameters, and further knew well the characteristic of the welding process.
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