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51.
本文研究具有随机扰动的哈密顿系统的重现现象,尤其是轨道随机周期变差解和近不变环面解.具体来说,对线性薛定谔方程,我们完整阐述了随机周期变差解何时存在;对随机扰动的近可积哈密顿系统,我们证明了近不变环面的存在性与驱动噪声对应的哈密顿函数的对合性相关. 相似文献
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虫害检测算法研究是开展虫害快速、准确监测,制定精准森防检疫措施的重要基础。以毛竹叶片为研究尺度,基于刚竹毒蛾危害下的寄主外部形态与内部生理现象总结,选择并实测叶损量LL、相对叶绿素含量RCC、相对含水量RWC、原始光谱的733.66~898.56 nm值(ρ733.66~898.56)、一阶微分光谱的562.95~585.25 nm值(ρ′562.95~585.25)与706.18~725.41 nm值(ρ′706.18~725.41)等理化参数,随机划分实验组(63组)和验证组(37组)并设计5次重复实验;分别运用Fisher判别分析、BP神经网络、随机森林等三种方法建立刚竹毒蛾危害等级的检测模型,从检测精度、Kappa系数及R2等指标对模型的检测效果予以分析和比较。结果显示,Fisher判别分析、BP神经网络、随机森林的检测精度分别为69.19%,65.41%,83.78%,Kappa系数分别为0.576 9,0.532 4和0.778 8,R2分别为0.722 2,0.582 6和0.870 9,总体而言,三种方法均具备刚竹毒蛾危害的检测能力,随机森林的检测效果最优,Fisher判别分析次之,再次为BP神经网络;从分等级来看,随机森林的检测精度亦优于Fisher判别分析与BP神经网络,但3种方法对中度危害等级的检测精度均有所不足。该成果可为刚竹毒蛾危害及其他病虫害检测算法的选择提供参考,并为进一步建立冠层、遥感影像像元等尺度的虫害检测模型奠定基础。 相似文献
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The identification of disease-relevant genes represents a challenge in microarray-based disease diagnosis where the sample size is often limited. Among established methods, reversible jump Markov Chain Monte Carlo (RJMCMC) methods have proven to be quite promising for variable selection. However, the design and application of an RJMCMC algorithm requires, for example, special criteria for prior distributions. Also, the simulation from joint posterior distributions of models is computationally extensive, and may even be mathematically intractable. These disadvantages may limit the applications of RJMCMC algorithms. Therefore, the development of algorithms that possess the advantages of RJMCMC methods and are also efficient and easy to follow for selecting disease-associated genes is required. Here we report a RJMCMC-like method, called random frog that possesses the advantages of RJMCMC methods and is much easier to implement. Using the colon and the estrogen gene expression datasets, we show that random frog is effective in identifying discriminating genes. The top 2 ranked genes for colon and estrogen are Z50753, U00968, and Y10871_at, Z22536_at, respectively. (The source codes with GNU General Public License Version 2.0 are freely available to non-commercial users at: http://code.google.com/p/randomfrog/.) 相似文献
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《Physics letters. A》2014,378(38-39):2831-2844
A new global stochastic search, guided mainly through derivative-free directional information computable from the sample statistical moments of the design variables within a Monte Carlo setup, is proposed. The search is aided by imparting to the directional update term additional layers of random perturbations referred to as ‘coalescence’ and ‘scrambling’. A selection step, constituting yet another avenue for random perturbation, completes the global search. The direction-driven nature of the search is manifest in the local extremization and coalescence components, which are posed as martingale problems that yield gain-like update terms upon discretization. As anticipated and numerically demonstrated, to a limited extent, against the problem of parameter recovery given the chaotic response histories of a couple of nonlinear oscillators, the proposed method appears to offer a more rational, more accurate and faster alternative to most available evolutionary schemes, prominently the particle swarm optimization. 相似文献
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For a spatial characteristic, there exist commonly fat-tail frequency distributions of fragment-size and -mass of glass, areas enclosed by city roads, and pore size/volume in random packings. In order to give a new analytical approach for the distributions, we consider a simple model which constructs a fractal-like hierarchical network based on random divisions of rectangles. The stochastic process makes a Markov chain and corresponds to directional random walks with splitting into four particles. We derive a combinatorial analytical form and its continuous approximation for the distribution of rectangle areas, and numerically show a good fitting with the actual distribution in the averaging behavior of the divisions. 相似文献
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Ion Grama Ronan Lauvergnat Émile Le Page 《Stochastic Processes and their Applications》2019,129(7):2485-2527
Let be a branching process in a random environment defined by a Markov chain with values in a finite state space . Let be the probability law generated by the trajectories of starting at We study the asymptotic behaviour of the joint survival probability , as in the critical and strongly, intermediate and weakly subcritical cases. 相似文献