meteorological stations usually contain some missing data for different reasons.there are several traditional methods for completing data, among them bivariate and multivariate linear and non-linear correlation analysis, double mass curve, ratio and difference methods, moving average and probability density functions are commonly used. in this paper a blended model comprising the bivariate expo...

Markov Pro ess in the Rare Transitions Regime Chandra Nair Dept. of Ele t. Engg. Stanford University Stanford CA 94305, USA m handra stanford.edu Erik Ordentli h Information Theory Resear h Group HP Laboratories Palo Alto CA 94304, USA erik.ordentli h hp. om Tsa hy Weissman Dept. of Ele t. Engg. Stanford University Stanford CA 94305, USA tsa hy stanford.edu Abstra t—Re ent work by Ordentli h an...

Biocapacity evaluation is an important part of sustainable development research, but quantitative and spatial future scenario analysis still have model methodological difficulties. Based on the high-resolution Globeland30 dataset, authors analyzed characteristics land use/cover changes Loess Plateau in Northern Shaanxi from 2000 to 2020. Then, comprehensively considering driving factors social ...

Land use change is one of the most important scientific research themes in the field of global environmental change. Due to the presence of uncertainty and randomness in the real world, it is difficult to simulate land use change exactly. To address the spatial uncertainty and temporal randomness in land use change, we propose a model for simulating land use change based on Markov chain and cel...

We consider a complex system composed of many non-identical parts where (i) the dynamics of each part are Ornstein–Uhlenbeck; (ii) all parts are driven by a common external Lévy noise; and (iii) the system’s collective output is the averaged aggregate of the outputs of its parts. Whereas the dynamics on the ‘microscopic’ parts-level are Markov, the dynamics on the ‘macroscopic’ system-level are...