A LARGE DEVIATION PRINCIPLE FOR THE STOCHASTIC GENERALIZED GINZBURG-LANDAU EQUATION DRIVEN BY JUMP NOISE

In this paper,we establish a large deviation principle for the stochastic generalized Ginzburg-Landau equation driven by jump noise.The main difficulties come from the highly non-linear coefficient and the jump noise.Here,we adopt a new sufficient condition for the weak convergence criterion of the large deviation principle,which was initially proposed by Matoussi,Sabbagh and Zhang(2021).

GENERALIZED STOCHASTIC DURATION INMARKOVIAN HEATH-JARROW-MORTONFRAMEWORK

This paper focuses on how to measure the interest rate risk. The conventional measure methods of interest rate risk are reviewed and the duration concept is generalized to stochastic duration in the Markovian HJM framework. The generalized stochastic duration of the coupon bond is defined as the time to maturity of a zero coupon bond having the same instantaneous variance as the coupon bond. According to this definition., the authors first present the framework of Markovian HJM model, then deduce the measures of stochastic duration in some special cases which cover some extant interest term structure.

Asymptotic behavior of 2D generalized stochastic Ginzburg-Landau equation with additive noise

The 2D generalized stochastic Ginzburg-Landau equation with additive noise is considered. The compactness of the random dynamical system is established with a priori estimate method, showing that the random dynamical system possesses a random attractor in H^1 0.

A New Conjugate Gradient Projection Method for Solving Stochastic Generalized Linear Complementarity Problems

In this paper, a class of the stochastic generalized linear complementarity problems with finitely many elements is proposed for the first time. Based on the Fischer-Burmeister function, a new conjugate gradient projection method is given for solving the stochastic generalized linear complementarity problems. The global convergence of the conjugate gradient projection method is proved and the related numerical results are also reported.

Stability and Stabilization on Generalized Delay Stochastic Neural Network with Distributed Parameter

Inner stability and stabilization of Cohen-Grossberg generalized delay stochastic neural network with distributed parameter are discussed. The main method adopted is, combining inequality techniques, to apply Ito differential formula to the constructed average function with respect to spatial variables along the system considered under the integral operator. Some sufficient conditions are given.

Exponential stability of stochastic generalized porous media equations with jump

Stochastic generalized porous media equation with jump is considered. The aim is to show the moment exponential stability and the almost certain exponential stability of the stochastic equation.

MODELING AND PERFORMANCE ANALYSIS FOR THE SERIAL AND PARALLEL PRODUCTION SYSTEM BASED ON GSPN

Differed from the existed applications of generalized stochastic Petri net(GSPN) theory in machine-tool manufacturing system, reliability computation of FMS, testabilityparameters determination and fault analysis, a new idea of applying GSPN to model and performanceanalysis for the serial and parallel production system is proposed. And one typical discrete eventdynamic system (DEDS), turner-unit of palletizing system, is taken as a real case to research. Basedupon the established GSPN models, the working performances of serial and parallel layout arecompared. Furthermore, their differences of working mechanisms including feeding mechanism,coordinating mechanism and monitoring mechanism are discussed. Thus the theoretical basis which ishelpful to appraise layout plan and its reasonableness is provided. Meanwhile, the research resultsshow that parallel layout is more advantageous to greatly improve the operational speed ofproduction system than serial one.

MAXIMUM PRINCIPLE FOR STOCHASTIC OPTIMAL CONTROL PROBLEM WITH DISTRIBUTED DELAYS

This paper is concerned with a Pontryagin's maximum principle for the stochastic optimal control problem with distributed delays given by integrals of not necessarily linear functions of state or control variables.By virtue of the duality method and the generalized anticipated backward stochastic differential equations,we establish a necessary maximum principle and a sufficient verification theorem.In particular,we deal with the controlled stochastic system where the distributed delays enter both the state and the control.To explain the theoretical results,we apply them to a dynamic advertising problem.

Temporal Statistical Downscaling of Precipitation and Temperature Forecasts Using a Stochastic Weather Generator

Statistical downscaling is based on the fact that the large-scale climatic state and regional/local physiographic features control the regional climate. In the present paper, a stochastic weather generator is applied to seasonal precipitation and temperature forecasts produced by the International Research Institute for Climate and Society （IRI）. In conjunction with the GLM （generalized linear modeling） weather generator, a resampling scheme is used to translate the uncertainty in the seasonal forecasts （the IRI format only specifies probabilities for three categories： below normal, near normal, and above normal） into the corresponding uncertainty for the daily weather statistics. The method is able to generate potentially useful shifts in the probability distributions of seasonally aggregated precipitation and minimum and maximum temperature, as well as more meaningful daily weather statistics for crop yields, such as the number of dry days and the amount of precipitation on wet days. The approach is extended to the case of climate change scenarios, treating a hypothetical return to a previously observed drier regime in the Pampas.

Visual Programming of Stochastic Weather Generator and Future Applications on Agroecological Study

Based on former studies on weather simulator modules in IPMist laboratory, study on visual programming of stochastic weather generator(VS-WGEN)was continued. In this study, Markov Chain, Monte Carlo, Fourier Series, and weak stationary process were used to generate the daily weather data in software Matlab 6. 0, with the data input from 40 years' weather data recorded by Beijing Weather Station. The generated data includes daily maximum temperature, minimum temperature, precipitation and solar radiation. It has been verified that the weather data generated by the VS-WGEN were more accurate than that by the old WGEN, when twenty new model parameters were included. VS-WGEN has wide software applications, such as pest risk analysis, pest forecast and management. It can be implemented in hardware development as well, such as weather control in weather chamber and greenhouse for researches on ecological adaptation of crop varieties to a given location over time and space. Overall, VS-WGEN is a very useful tool for studies on theoretical and applied ecology.

STOCHASTIC VARIATIONAL INEQUALITY APPROACHES TO THE STOCHASTIC GENERALIZED NASH EQUILIBRIUM WITH SHARED CONSTRAINTS

In this paper,we consider the generalized Nash equilibrium with shared constraints in the stochastic environment,and we call it the stochastic generalized Nash equilibrium.The stochastic variational inequalities are employed to solve this kind of problems,and the expected residual minimization model and the conditional value-at-risk formulations defined by the residual function for the stochastic variational inequalities are discussed.We show the risk for different kinds of solutions for the stochastic generalized Nash equilibrium by the conditional value-at-risk formulations.The properties of the stochastic quadratic generalized Nash equilibrium are shown.The smoothing approximations for the expected residual minimization formulation and the conditional value-at-risk formulation are employed.Moreover,we establish the gradient consistency for the measurable smoothing functions and the integrable functions under some suitable conditions,and we also analyze the properties of the formulations.Numerical results for the applications arising from the electricity market model illustrate that the solutions for the stochastic generalized Nash equilibrium given by the ERM model have good properties,such as robustness,low risk and so on.

Anti-Attacking Modeling and Analysis of Cyberspace Mimic DNS

With the rapid development of information technology,the cyberspace security problem is increasingly serious.Kinds of dynamic defense technology have emerged such as moving target defense and mimic defense.This paper aims to describe the architecture and analyze the performance of Cyberspace Mimic DNS based on generalized stochastic Petri net.We propose a general method of anti-attacking analysis.For general attack and special attack model,the available probability,escaped probability and nonspecial awareness probability are adopted to quantitatively analyze the system performance.And we expand the GSPN model to adjust to engineering practice by specifying randomness of different output vectors.The result shows that the proposed method is effective,and Mimic system has high anti-attacking performance.To deal with the special attack,we can integrate the traditional defense mechanism in engineering practice.Besides,we analyze the performance of mimic DNSframework based on multi-ruling proxy and input-output desperation,the results represent we can use multi ruling or high-speed cache servers to achieve the consistent cost of delay,throughput compared with single authorized DNS,it can effectively solve 10%to 20%performance loss caused by general ruling proxy.

Changes in climatic variability and maize yield inNortheast China

The method linking general circulation models' (GCMs') outputs with crop growthsimulation models' inputs has been the first choice in the studies of impacts of climate change.Changes in climatic variability, however were not considered in most studies due to limitedknowledge concerned Changes in climatic means derived from a general circulation model DKRZOPYC were input into a stochastic weather generator WGEN run for synthetic daily climate scenarios.Monte Carlo stochastic sampling method was adopted to generate climate change scenarios withvarious possible climatic veriabilities. A dynamic simulation model for maize growth anddevelopment of MZMOD was used to assess the potenhal implication of the changes in both climaticmeans and variability nd the boacts of crop management in changing climate on maize productionin Northeast China. The results indicated that maize yield would be reduced to various degrees inmost of the sensitivity experiments of climatic variability associating with the shortening of theduration of phenological phase of different sowing dates. The Anpacts of the diverse distributions ofclimatic factors detetmined by multiple changes in climatic variability on maire production and itsvariation, however, are not identical and have distinct regional disparities. Yield reduction caused bychanges in climatic means may be alleviated or aggravated by didributions of certain climaticvariables in line with the corresponding climatic variability according to the sensitivity analyses.Consequently, the hypothesis keeping climatic variability constant in the traditional research imposesrestriction on the overall inveshgation of the impacts of climate change on maize production.

Effects of temperature change on the rheological property of modified multiwall carbon nanotubes

Solvent-free nanofluids hold promise for many technologically significant applications.The liquid-like behavior,a typical rheological property of solvent-free nanofluids,has aroused considerable interests.However,there has been still lack of efficient methods to predict and control the liquid-like behavior of solvent-free nanofluids.In this paper,we propose a semi-discrete dynamic system with stochastic excitation describing the temperature change effects on the rheological property of multiwall carbon nanotubes(MWCNTs)modified by grafting sulfonic acid terminated organosilanes as corona and tertiary amine as canopy,which is a typical covalent-type solvent-free nanofluid system.The vibration of the grafting branches is simulated by employing a structure-preserving approach,and the shear force of grafting branches at the fixed end is computed subsequently.By taking the shear forces as an excitation acting on the MWCNTs,the axial motion of the MWCNTs is solved with the 7-point Gauss-Kronrod quadrature rule.The critical temperature associated with the appearance of the liquid-like behavior as well as the upper bound of the moving speed of the modified MWCNTs is determined,which can be used to predict and control the liquid-like behavior of the modified MWCNTs in engineering applications.

On the Generalized 2-D Stochastic Ginzburg-Landau Equation

This paper proves the existence and uniqueness of solutions in a Banach space for the generalized stochastic Ginzburg-Landau equation with a multiplicative noise in two spatial dimensions. The noise is white in time and correlated in spatial variables. The condition on the parameters is the same as in the deterministic case. The Banach contraction principle and stochastic estimates in Banach spaces are used as the main tool.

The Cauchy problem for the stochastic generalized Benjamin-Ono equation

The current paper is devoted to the Cauchy problem for the stochastic generalized Benjamin-Ono equation.By establishing the bilinear and trilinear estimates in some Bourgain spaces,we prove that the Cauchy problem for the stochastic generalized Benjamin-Ono equation is locally well-posed for the initial data u0(x,w)∈L^(2)(Ω;H^(s)(R))which is F0-measurable with s≥1/2-α/4 andΦ∈L20,s.In particular,whenα=1,we prove that it is globally well-posed for the initial data u0(x,w)∈L2(Ω;H1(R))which is F0-measurable andΦ∈L20,1.The key ingredients that we use in this paper are trilinear estimates,the Ito formula and the Burkholder-Davis-Gundy(BDG)inequality as well as the stopping time technique.

A study on the possible impacts of climate warming on rice production in China

Based on climate change scenarios projected from GCMs (GFDL, UKMO and MPI), this study evaluates possible impacts of climate warming on rice production in China using numerical simulation experiments. A stochastic weather generator is used to make the projected climatic change scenarios suitable to the input of crop model, ORYZA1. The results show that the duration of rice growing season will be lengthened by 6-11 days and the accumulated temperature will increase by 200℃.d-330℃.d when CO2 concentration in the atmosphere doubles. The probability of cool injury in reproductive and grain filling period will decrease while that of heat stress will increase. Rice yield will decrease if cultivars and fanning practices are unchanged. If the dates of rice development stages can be maintained unchanged through cultivar adjustment although rice yield in most parts of the areas will decrease, the decrements will be much less than that when cultivars and farming practices are unchanged.

End-of-Life Decision making in circular economy using generalized colored stochastic Petri nets

Circular economy enables to restore product value at the end of life i.e.when no longer used or damaged.Thus,the product life cycle is extended and this economy permits to reduce waste increase and resources rarefaction.There are several revaluation options(reuse,remanufacturing,recycling,...).So,decisionmakers need to assess these options to determine which is the best decision.Thus,we will present a study about an End-Of-Life(EoL)decision making which aims to facilitate the industrialization of circular economy.For this,it is essential to consider all variables and parameters impacting the decision of the product trajectory.A first part of the work proposes to identify the variables and parameters impacting the decision making.A second part proposes an assessment approach based on a modeling by Generalized Colored Stochastic Petri Net(GCSPN)and on a Monte-Carlo simulation.The approach developed is tested on an industrial example from the literature to analyze the efficiency and effectiveness of the model.This first application showed the feasibility of the approach,and also the limits of the GCSPN modelling.

Reliability and safety analysis of redundant vehicle management computer system

Redundant techniques are widely adopted in vehicle management computer （VMC） to ensure that VMC has high reliability and safety. At the same time, it makes VMC have special characteristics, e.g., failure correlation, event simultaneity, and failure self-recovery. Accordingly, the reliability and safety analysis to redundant VMC system （RVMCS） becomes more difficult. Aimed at the difficulties in RVMCS reliability modeling, this paper adopts generalized stochastic Petri nets to establish the reliability and safety models of RVMCS. Then this paper analyzes RVMCS oper- ating states and potential threats to flight control system. It is verified by simulation that the reli- ability of VMC is not the product of hardware reliability and software reliability, and the interactions between hardware and software faults can reduce the real reliability of VMC obviously. Furthermore, the failure undetected states and false alarming states inevitably exist in RVMCS due to the influences of limited fault monitoring coverage and false alarming probability of fault mon- itoring devices （FMD）. RVMCS operating in some failure undetected states will produce fatal threats to the safety of flight control system. RVMCS operating in some false alarming states will reduce utility of RVMCS obviously. The results abstracted in this paper can guide reliable VMC and efficient FMD designs. The methods adopted in this paper can also be used to analyze other intelligent systems＇ reliability.

Modeling of reliability and performance assessment of a dissimilar redundancy actuation system with failure monitoring

Actuation system is a vital system in an aircraft, providing the force necessary to move flight control surfaces. The system has a significant influence on the overall aircraft performance and its safety. In order to further increase already high reliability and safety, Airbus has imple- mented a dissimilar redundancy actuation system （DRAS） in its aircraft. The DRAS consists of a hydraulic actuation system （HAS） and an electro-hydrostatic actuation system （EHAS）, in which the HAS utilizes a hydraulic source （HS） to move the control surface and the EHAS utilizes an elec- trical supply （ES） to provide the motion force. This paper focuses on the performance degradation processes and fault monitoring strategies of the DRAS, establishes its reliability model based on the generalized stochastic Petri nets （GSPN）, and carries out a reliability assessment considering the fault monitoring coverage rate and the false alarm rate. The results indicate that the proposed reli- ability model of the DRAS, considering the fault and redundancy degradation process and identify monitoring, can express its fault logical relation potential safety hazards.