Detecting physical laws from data of stochastic dynamical systems perturbed by non-Gaussianα-stable Lévy noise

Massive data from observations,experiments and simulations of dynamical models in scientific and engineering fields make it desirable for data-driven methods to extract basic laws of these models.We present a novel method to identify such high dimensional stochastic dynamical systems that are perturbed by a non-Gaussianα-stable Lévy noise.More explicitly,firstly a machine learning framework to solve the sparse regression problem is established to grasp the drift terms through one of nonlocal Kramers–Moyal formulas.Then the jump measure and intensity of the noise are disposed by the relationship with statistical characteristics of the process.Three examples are then given to demonstrate the feasibility.This approach proposes an effective way to understand the complex phenomena of systems under non-Gaussian fluctuations and illuminates some insights into the exploration for further typical dynamical indicators such as the maximum likelihood transition path or mean exit time of these stochastic systems.

Lévy过程驱动的随机二维Navier-Stokes方程解的指数性态(英文)

本文研究了Lévy过程驱动的随机二维Navier-Stokes方程弱解的指数性态.给出了不同条件下解的长时间形态,获得了一些特殊情形下解的样本轨道的指数稳定性.

Periodic dividends and capital injections for a spectrally negative Lévy risk process under absolute ruin

The spectrally negative Lévy risk model with random observation times is considered in this paper,in which both dividends and capital injections are made at some independent Poisson observation times.Under the absolute ruin,the expected discounted dividends and the expected discounted capital injections are discussed.We also study the joint Laplace transforms including the absolute ruin time and the total dividends or the total capital injections.All the results are expressed in scale functions.

马尔可夫交换Lévy过程模型下的期权定价及其对冲（英文）

In this paper, we consider a Markov switching Lévy process model in which the underlying risky assets are driven by the stochastic exponential of Markov switching Lévy process and then apply the model to option pricing and hedging. In this model, the market interest rate, the volatility of the underlying risky assets and the N-state compensator,depend on unobservable states of the economy which are modeled by a continuous-time Hidden Markov process. We use the MEMM(minimal entropy martingale measure) as the equivalent martingale measure. The option price using this model is obtained by the Fourier transform method. We obtain a closed-form solution for the hedge ratio by applying the local risk minimizing hedging.

Quantifying the parameter dependent basin of the unsafe regime of asymmetric Lévy-noise-induced critical transitions

In real systems,the unpredictable jump changes of the random environment can induce the critical transitions(CTs)between two non-adjacent states,which are more catastrophic.Taking an asymmetric Lévy-noise-induced tri-stable model with desirable,sub-desirable,and undesirable states as a prototype class of real systems,a prediction of the noise-induced CTs from the desirable state directly to the undesirable one is carried out.We first calculate the region that the current state of the given model is absorbed into the undesirable state based on the escape probability,which is named as the absorbed region.Then,a new concept of the parameter dependent basin of the unsafe regime(PDBUR)under the asymmetric Lévy noise is introduced.It is an efficient tool for approximately quantifying the ranges of the parameters,where the noise-induced CTs from the desirable state directly to the undesirable one may occur.More importantly,it may provide theoretical guidance for us to adopt some measures to avert a noise-induced catastrophic CT.

Simulation of a Daily Precipitation Time Series Using a Stochastic Model with Filtering

After we modified raw data for anomalies, we conducted spectral analysis using the data. In the frequency, the spectrum is best described by a decaying exponential function. For this reason, stochastic models characterized by a spectrum attenuated according to a power law cannot be used to model precipitation anomaly. We introduced a new model, the e-model, which properly reproduces the spectrum of the precipitation anomaly. After using the data to infer the parameter values of the e-model, we used the e-model to generate synthetic daily precipitation time series. Comparison with recorded data shows a good agreement. This e-model resembles fractional Brown motion (fBm)/fractional Lévy motion (fLm), especially the spectral method. That is, we transform white noise Xt to the precipitation daily time series. Our analyses show that the frequency of extreme precipitation events is best described by a Lévy law and cannot be accounted with a Gaussian distribution.

Lévy Flights, 1/<i>f </i>Noise and Self Organized Criticality

A new analysis of a previously studied traveling agent model, showed that there is a relation between the degree of homogeneity of the medium where the agents move, agent motion patterns, and the noise generated from their displacements. We proved that for a particular value of homogeneity, the system self organizes in a state where the agents carry out Lévy walks and the displacement signal corresponds to 1/f noise. Using probabilistic arguments, we conjectured that 1/f noise is a fingerprint of a statistical phase transition, from randomness (disorder) to predictability (order), and that it emerges from the contextuality nature of the system which generates it.

Modal identification of system driven by lévy random excitation based on continuous time AR model

Based on the continuous time AR model,this paper presents a new time-domain modal identification method of LTI system driven by the uniformly modulated lévy random excitation.The structural dynamic equation is first transformed into the observation equation and the state equation(namely,stochastic differential equation).Based on the property of the strong solution of the stochastic differential equation,the uniformly modulated function is identified piecewise.Then by virtue of the Girsanov theorem,we present the exact maximum likelihood estimators of parameters.Finally,the modal parameters are identified by eigen analysis.Numerical results show that the method not only has high precision and robustness but also has very high computing efficiency.

水稻栽后前期根系与地上部增重模型及相互关系

以＂冈优22＂、＂Ⅱ优162＂和＂K优047＂为材料,通过裂区试验设置不同种植方式研究了水稻秧苗移栽后根系与地上部增重模型及其相互关系。结果表明：秧苗移栽至拔节期,根系增重和地上部干物质积累均呈指数模型增加,根系模型的相关指数在0.98以上,地上部模型的相关指数在0.94以上。地上部干重与根重间存在极显著的线性相关关系。根冠比在移栽后开始上升,至栽后10~15 d时达到最大值,然后下降,呈单峰曲线。3种种植方式中,免耕高留茬抛秧地上部和根系干重均最低,移栽后前期生长最慢,但根冠比要高于常耕插秧处理。3个品种中,＂冈优22＂根系和地上部干物质积累量最高,＂Ⅱ优162＂的根冠比最大。

考虑电压稳定约束的最优潮流

采用指数负荷模型研究了有载调压变压器对系统最优潮流的影响。在阐述电压稳定性L指标的基础上,将L指标引入传统最优潮流中形成电压稳定约束的最优潮流,运用原-对偶内点法求解该模型。算例结果表明,该模型鲁棒性较好,能更加真实地反映系统实际运行情况。不同静态负荷模型对系统电压稳定性和经济性有一定的影响,系统电压稳定性的提高是以牺牲经济性为代价的,在考虑电压稳定性时,有载调压变压器的加入可以有效降低系统燃料费用,平抑系统有功出力和燃料费用的波动,将波动维持在一个较小的范围内。

Differential Evolution-Boosted Sine Cosine Golden Eagle Optimizer with Lévy Flight

Golden eagle optimizer(GEO)is a recently introduced nature-inspired metaheuristic algorithm,which simulates the spiral hunting behavior of golden eagles in nature.Regrettably,the GEO suffers from the challenges of low diversity,slow iteration speed,and stagnation in local optimization when dealing with complicated optimization problems.To ameliorate these deficiencies,an improved hybrid GEO called IGEO,combined with Lévy flight,sine cosine algorithm and differential evolution(DE)strategy,is developed in this paper.The Lévy flight strategy is introduced into the initial stage to increase the diversity of the golden eagle population and make the initial population more abundant;meanwhile,the sine-cosine function can enhance the exploration ability of GEO and decrease the possibility of GEO falling into the local optima.Furthermore,the DE strategy is used in the exploration and exploitation stage to improve accuracy and convergence speed of GEO.Finally,the superiority of the presented IGEO are comprehensively verified by comparing GEO and several state-of-the-art algorithms using(1)the CEC 2017 and CEC 2019 benchmark functions and(2)5 real-world engineering problems respectively.The comparison results demonstrate that the proposed IGEO is a powerful and attractive alternative for solving engineering optimization problems.

菊芋光响应曲线最佳模型选择及其环境适应性

为揭示菊芋的光合特性,以草地、林下两种不同生长环境的菊芋(Helianthus tuberosus L.)为研究对象,利用便携式光合仪LI-6400进行光响应曲线的测量,并选取最佳拟合模型,计算并对比两种环境条件下的光合参数,深入分析菊芋生理生长特性与生长环境间的关系。结果表明:改进指数模型为菊芋的光响应曲线最佳拟合模型,拟合所得R^2为0.999,光饱和点(I_(sat))为1 600μmol·m^(-2)·s^(-1))、光补偿点(I_c)为37.637μmol·m^(-2)·s^(-1))、最大净光合速率(P_(max))为27.256μmol·m^(-2)·s^(-1))、暗呼吸速率(Rd)为-2.218μmol·m^(-2)·s^(-1)),初始量子效率(φ)为0.059;菊芋为阳生植物,耐高温耐干旱;因此菊芋应种植在高温干燥的生境中,草地更适宜于菊芋的生存。

A FAST AND HIGH ACCURACY NUMERICAL SIMULATION FOR A FRACTIONAL BLACK-SCHOLES MODEL ON TWO ASSETS

In this paper,a two dimensional(2D)fractional Black-Scholes(FBS)model on two assets following independent geometric Lévy processes is solved numerically.A high order convergent implicit difference scheme is constructed and detailed numerical analysis is established.The fractional derivative is a quasidifferential operator,whose nonlocal nature yields a dense lower Hessenberg block coefficient matrix.In order to speed up calculation and save storage space,a fast bi-conjugate gradient stabilized(FBi-CGSTAB)method is proposed to solve the resultant linear system.Finally,one example with a known exact solution is provided to assess the effectiveness and efficiency of the presented fast numerical technique.The pricing of a European Call-on-Min option is showed in the other example,in which the influence of fractional derivative order and volatility on the 2D FBS model is revealed by comparing with the classical 2D B-S model.