Multi–regime models for nonlinear nonstationary time series

Nonlinear nonstationary models for time series are considered, where the series is generated from an autoregressive equation whose coefficients change both according to time and the delayed values of the series itself, switching between several regimes. The transition from one regime to the next one may be discontinuous (self-exciting threshold model), smooth (smooth transition model) or continuous linear (piecewise linear threshold model). A genetic algorithm for identifying and estimating such models is proposed, and its behavior is evaluated through a simulation study and application to temperature data and a financial index.     

专利申请与授权量的时间序列分析

专利的申请和授权量动态分析与预测是建立专利预警机制、设计与制定相关政策和战略的基础,具有重要的理论意义。起伏型时间序列法是一种新的时间序列分析法,提出用起伏型时间序列法对专利申请与授权数据进行动态分析。以2005年国内专利申请与授权数量月动态为研究数据,对专利申请、授权及发明专利申请数量的月动态进行建模模拟,结果令人满意,说明起伏型时间序列分析方法可应用于专利申请与授权动态模拟,从而丰富了专利申请与授权数据动态分析方法。     

Thermomechanical modeling and simulation of aluminum alloys during extrusion process

The purpose of this work is to simulate the microstructure development of aluminum alloys during hot metal forming processes such as extrusion with the help of the Finite Element Method (FEM). To model the thermomechanical coupled behavior of the material during the extrusion process an appropriate material model is required. In the current work a Johnson–Cook like thermoelastic viscoplastic material model is used. To overcome the numerical difficulties during simulation of extrusion such as contact problem and element distortion an adaptive meshing system is developed and applied. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Dynamics and chaos control of the self-sustained electromechanical device with and without discontinuity

In this paper, we consider the dynamics and chaos control of the self-sustained electromechanical device with and without discontinuity. The amplitude equations are derived in the general case using the harmonic balance method. The model without discontinuity is first considered. The effects of the amplitude of the parametric modulation and some particular coefficients are found in the response curves. The transition to chaotic behavior is found using numerical simulations of the equations of motion. We find that chaos appears in the model between the quasi-periodic and periodic orbits when the amplitude of the external excitation E₀ vary. An adaptive Lyapunov control strategy enables us to drive the system from the chaotic states to a targeting periodic orbit. The effects of elasticity and damping on the dynamics of the self-sustained electromechanical system are also derived.     

Ab-initio molecular dynamics simulation on nano-system under external pressure

A new constant-pressure molecular dynamics (MD) method is developed to simulate the dynamic behavior and structure transition of finite system under external pressure. In this method, no artificial parameter is introduced and the computation overheads are very small. As an application, a hard-soft transition of single wall carbon nanotube     

Ab-<Emphasis Type="Italic">initio</Emphasis> molecular dynamics simulation on nano-system under external pressure

A new constant-pressure molecular dynamics (MD) method is developed to simulate the dynamic behavior and structure transition of finite system under external pressure. In this method, no artificial parameter is introduced and the computation overheads are very small. As an application, a hard-soft transition of single wall carbon nanotube (SWCNT) under external pressure is found, which is in agreement with the experiments.     

Disturbance rejection in robust PdE-based MRAC laws for uncertain heterogeneous multiagent networks under boundary reference

Disturbance is a pervasive source of uncertainty in most applications. This paper presents model reference adaptive control (MRAC) laws for uncertain multiagent networks with a disturbance rejection capability. The algorithms proposed can also be viewed as the extension of the robust model reference adaptive control (MRAC) laws with disturbance rejection recently derived for systems described by parabolic and hyperbolic partial differential equations (PDEs) with spatially-varying parameters under distributed sensing and actuation to heterogeneous multiagent networks characterized by parameter uncertainty. The latter extension is carried out using partial difference equations (PdEs) on graphs that preserve parabolic and hyperbolic like cumulative network behavior. Unlike in the PDE case, only boundary input is specified for the reference model. The algorithms proposed directly incorporate this boundary reference input into the reference PdE to generate the distributed admissible reference evolution profile followed by the agents. The agent evolution thus depends only on the interaction with the adjacent agents, making the system fully decentralized. Numerical examples are presented as well. The resulting PdE MRAC laws inherit the robust linear structure of their PDE counterparts.     

Ab-initio molecular dynamics simulation on nano-system under external pressure

A new constant-pressure molecular dynamics (MD) method is developed to simulate the dynamic behavior and structure transition of finite system under external pressure. In this method, no artificial parameter is introduced and the computation overheads are very small. As an application, a hard-soft transition of single wall carbon nanotube (SWCNT) under external pressure is found, which is in agreement with the experiments.

     

An adaptive stochastic model for financial markets

An adaptive stochastic model is introduced to simulate the behavior of real asset markets. The model adapts itself by changing its parameters automatically on the basis of the recent historical data. The basic idea underlying the model is that a random variable uniformly distributed within an interval with variable extremes can replicate the histograms of asset returns. These extremes are calculated according to the arrival of new market information. This adaptive model is applied to the daily returns of three well-known indices: Ibex35, Dow Jones and Nikkei, for three complete years. The model reproduces the histograms of the studied indices as well as their autocorrelation structures. It produces the same fat tails and the same power laws, with exactly the same exponents, as in the real indices. In addition, the model shows a great adaptation capability, anticipating the volatility evolution and showing the same volatility clusters observed in the assets. This approach provides a novel way to model asset markets with internal dynamics which changes quickly with time, making it impossible to define a fixed model to fit the empirical observations.     

Crisis-induced chaos in the Rose-Hindmarsh model for neuronal activity

The bifurcation diagrams for the Rose-Hindmarsh model are obtained from the Poincaré maps which govern the dynamics of this differential system. The Lyapunov spectra for this model are estimated from time series. The transition from periodicity to crisis-induced chaos. and back to periodicity is presented for I [2.5, 2.69]. and is qualitatively different from the transitions described for different parameter regions [A. V. Holden and Yinshui Fan, Chaos, Solitons & Fractals 2, 221–236 (1992); Chaos, Solitons & Fractals 2, 349–369 (1992)]. A piecewise smooth, one-dimensional map is constructed to simulate the dynamics of the model and to reproduce the process of crisis-induced chaos.     

Melnikov analysis of chaos in a general epidemiological model

The purpose of this paper is to study a SIR model of epidemic dynamics with a periodically modulated nonlinear incidence rate. We must go, for the first time, through a series of coordinate transformations to bring the equations into amenable to Melnikov analysis. This analysis establishes mathematically the existence of chaotic motion of the models by Melnikov's method. The numerical simulations are made for the conclusions in this paper.     

Adaptive feedback controller for projective synchronization

Due to the unpredictability of the scaling factor of projective synchronization in coupled partially linear systems, it is hard to know for sure the terminal state of the synchronized dynamics. In this paper, a simple adaptive linear feedback control method is proposed for controlling the scaling factor onto a desired value, based on the invariance principle of differential equations. Firstly, we prove the synchronizability of the proposed simple adaptive projective synchronization control method from the viewpoint of mathematics. Then, two numerical examples are presented to illustrate the applications of the derived results. Finally, we propose a communication scheme based on the adaptive projective synchronization of the Lorenz chaotic system. Numerical simulation shows its feasibility.     

Time behavior of stressed nonhierarchical networks

In this paper it is shown, by means of simulation, that interesting time behavior is observed for damaged and overloaded networks, and that adaptive, decentralized intelligence can have a dramatic influence on the overall network performance. The time behavior of nonhierarchical networks is modeled by a system of nonlinear difference equations among global variables, and bistability is shown to exist. Using a simple adaptive control mechanism, it is shown that, depending upon the value of a certain network variable, either limit cycle or steady state behavior results. A few ideas are discussed for applications of nonhierarchical communications to cellular automata and to decision-making systems.     

A moving boundary problem derived from heat and water transfer processes in frozen and thawed soils and its numerical simulation

The seasonal change in depths of the frozen and thawed soils within their active layer is reduced to a moving boundary problem,which describes the dynamics of the total ice content using an independent mass balance equation and treats the soil frost/thaw depths as moving(sharp)interfaces governed by some Stefan-type moving boundary conditions,and hence simultaneously describes the liquid water and solid ice states as well as the positions of the frost/thaw depths in soil.An adaptive mesh method for the moving boundary problem is adopted to solve the relevant equations and to determine frost/thaw depths,water content and temperature distribution.A series of sensitivity experiments by the numerical model under the periodic sinusoidal upper boundary condition for temperature are conducted to validate the model,and to investigate the effiects of the model soil thickness,ground surface temperature,annual amplitude of ground surface temperature and thermal conductivity on frost/thaw depths and soil temperature.The simulated frost/thaw depths by the model with a periodical change of the upper boundary condition have the same period as that of the upper boundary condition,which shows that it can simulate the frost/thaw depths reasonably for a periodical forcing.     

A computational model for multi-agent E-commerce negotiations with adaptive negotiation behaviors

This paper presents a computational model to organize multi-agent E-commerce negotiations with adaptive negotiation behaviors aiming at enhancing the negotiation flexibilities of software agents. Firstly, the computational E-commerce negotiation model covering negotiation protocol, negotiation issues and negotiation strategies is specified to assist agents’ computing functions. Then, a three-staged adaptive negotiation behavior configuration mechanism is proposed to tackle the negotiation dynamics. In the pre-negotiation stage, agents’ negotiation behaviors are deployed by the case-based strategy assignment mechanism; in the on-going negotiation stage, opponents’ negotiation behaviors are tracked through the neural network learning model; in the post-negotiation stage, opponents’ concession functions are recorded using the time series measure. Finally, the computational negotiation model is tested through hypothetical negotiation cases. The outcomes show that the adaptive negotiation behavior configuration mechanism can benefit an agent to win more in the E-commerce negotiation.     

Robust autoregressive estimates using quadratic programming

The robust estimation of the autoregressive parameters is formulated in terms of the quadratic programming problem. This article's main contribution is to present an estimator that down weights both types of outliers in time series and improves the forecasting results. New robust estimates are yielded, by combining optimally two weight functions suitable for Innovation and Additive outliers in time series. The technique which is developed here is based on an approach of mathematical programming applications to I_p-approximation. The behavior of the estimators are illustrated numerically, under the additive outlier generating model. Monte Carlo results show that the proposed estimators compared favorably with respect to M-estimators and bounded influence estimators. Based on these results we conclude that one can improve the robust properties of AR(p) estimators using quadratic programming.     

Modeling,simulation and control a hydraulic servo system

Hydraulic actuators are widely used in industrial applications due to several advantages like large force and torque, high power to weight ratio, rapid and accurate response. In this paper a nonlinear model of a hydraulic servo system is developed by means of the associated differential equations and then simulated using Matlab techniques. The model describes the behavior of a servo system FESTO TP511 with MOOG-DDV633 servovalve and includes the nonlinearities of friction forces, valve dynamics, oil compressibility and load influence. The nonlinear model is used to design an optimal controller based on estimated state parameters through simulation. A digital control platform based on Atmel ATmega8535 microcontroller is used to compare the behavior of hydraulic system under PD and optimal control. The control platform was designed like an interface between PC and process: the control algorithm runs on PC and the digital platform assures amplifying, filtering and data communication functions. Both simulation and experimental results are provided to show the effectiveness of the proposed model and control method. (© 2006 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Computations of transport of pollutant in shallow water

The focus of this paper is to simulate the transport of a passive pollutant by a flow modelled by the two-dimensional shallow water equations. Considering the friction terms, new model for simulating the steady and unsteady transport of pollutant is established. Then the adaptive semi-discrete central-upwind scheme based on central weighted essentially non-oscillatory reconstruction is utilized for simulating the two-dimensional steady and unsteady transport of pollutant. The non-oscillatory behavior and accuracy of the scheme are demonstrated by the numerical result.