搜索结果: 31-45 共查到“知识库 环境与生态统计学”相关记录110条 . 查询时间(2.625 秒)
Fast dimension-reduced climate model calibration
Fast dimension-reduced climate model calibration
2013/4/27
What is the response of the climate system to anthropogenic forcings? This question is addressed typically using projections from climate models. The uncertainty surrounding current climate projection...
Classification with Asymmetric Label Noise: Consistency and Maximal Denoising
Classification Asymmetric Label Noise Consistency Maximal Denoising
2013/4/27
In many real-world classification problems, the labels of training examples are randomly corrupted. Previous theoretical work on classification with label noise assumes that the two classes are separa...
在经济社会活动中,由于人口、资源与环境的非公平分配引发了区域内的矛盾与冲突,从而制约了区域可持续发展。如何化解区域的矛盾与冲突,实现人口、资源与环境的公平性,本文试图以博弈论来研究这一问题。首先本文对区域内代际公共资源与环境公平性作博弈分析,揭示了若没有制度安排与约束,区域内非公平性、非协调性是普遍存在的现象。其次本文对区域内公共资源与环境公平性作博弈分析,揭示了代内公共资源与环境利用的非公平性。...
环保意识调查问卷的Logistic模型
logistic模型 方差分析
2013/8/22
本文应用多元统计分析中的方差分析,logistic模型等方法对环保意识调查问卷反馈的信息进行统计分析,建立被调查企业对环境保护意识的logistic模型,进而可对企业家的环境保护意识的好坏进行判断。
对环境经济核算的总体认识
环境经济核算 经济 环境
2013/8/22
环境经济核算缘起于两个相互联系的事实。事实之一是环境问题越来越深入地介入了人类的社会经济生活,成为国家和国际社会管理中共同面临的问题。在国际社会所倡导的可持续发展战略中,最重要的方面就是处理好经济、社会与环境之间的相互关系,尤其是经济发展与环境保护之间的关系。与上述事实相联系的另一个事实是,为管理所必须的信息数据系统不能满足可持续发展管理之需要,尚没有一个数据系统能够较好地反映出经济与环境之间的相...
试论环境统计学的建立
社会经济 国民经济 环境统计
2013/8/22
随着社会经济的发展,社会与环境、经济与环境之间的问题日益严重,已影响到整个国民经济的均衡发展,因此,对环境统计理论、指标体系的研究已引起了中国统计学界的重视。建立独立的环境统计学不仅对建立有中国特色的统计理论、方法体系有着重要意义,而且对于完善中国宏观经济统计监测系统,保持经济的可持续发展战略的实现,建立大统计学科有着重要的现实意义。本文拟就建立环境统计学有关的几个主要问题作初步的研究与探讨。
莺歌海—琼东南盆地构造-地层格架及南海动力变形分区
莺歌海盆地 琼东南盆地 挤出-逃逸构造区 古南海俯冲拖曳构造区 南海
2011/12/27
通过对盆地地震剖面构造-地层的详细解释,在莺歌海盆地和琼东南盆地(简称莺-琼盆地)古近纪同裂陷充填序列中识别出一条区域性的构造变革界面——T70,该界面在地震剖面上表现为显著的下削上超的地震反射结构特征,发育的时代为32~30 Ma,与南海海底扩张起始和红河断裂带左旋走滑的时间一致; T70界面将莺-琼盆地的同裂陷期地层分隔为断陷层和断坳层(琼东南盆地)或坳陷层(莺歌海盆地)两个构造-地层单元,这...
An estimation of distribution algorithm with adaptive Gibbs sampling for unconstrained global optimization
Estimation of distribution algorithms Evolutionary algorithms
2011/7/19
In this paper is proposed a new heuristic approach belonging to the field of evolutionary Estimation of Distribution Algorithms (EDAs). EDAs builds a probability model and a set of solutions is sample...
On non-stationary threshold autoregressive models
explosive TAR(1) model least-squares estimator unit root TAR(1) model
2011/7/19
In this paper we study the limiting distributions of the least-squares estimators for the non-stationary first-order threshold autoregressive (TAR(1)) model. It is proved that the limiting behaviors o...
Statistical methods of SNP data analysis with applications
Genetic data statistical analysis multifactor dimensiona-lity reduction
2011/7/7
Various statistical methods important for genetic analysis are considered and developed. Namely, we concentrate on the multifactor dimensionality reduction, logic regression, random forests and stocha...
Optimal Rate Scheduling via Utility-Maximization for J-User MIMO Markov Fading Wireless Channels with Cooperation
Processor-SharingQueues Random Environment Multi-Input Multi-Output
2011/7/7
We design a dynamic rate scheduling policy of Markov type via the solution (a social optimal Nash equilibrium point) to a utility-maximization problem over a randomly evolving capacity set for a class...
Markov Chain Monte Carlo Based on Deterministic Transformations
Geostatistics High dimension Inverse transfromation Jacobian
2011/7/6
In this article we propose a novel MCMC method based on deterministic transformations T : X x D --> X where X is the state-space and D is some set which may or may not be a subset of X. We refer to ou...
A method for generating realistic correlation matrices
method generating realistic correlation matrices
2011/7/6
Simulating sample correlation matrices is important in many areas of statistics. Approaches such as generating normal data and finding their sample correlation matrix or generating random uniform $[-1...
Nonasymptotic bounds on the estimation error of MCMC algorithms
Mean square error Computable bounds
2011/7/6
We address the problem of upper bounding the mean square error of MCMC estimators. Our analysis is non-asymptotic.