基于集对分析的城市生态足迹预测——以武汉市为例

自然生态环境是城市生态系统赖以生存和发展的重要物质基础，生态足迹作为生态环境承载状态测度的指标，受到社会、经济、人口等多种因素的影响，表现出时空动态性和不确定性特征。鉴于集对分析(SPA)在处理不确定性问题的优势，以武汉市为研究对象，将城市总生态足迹与其相关影响因子联系起来考虑，融合集对分析中的同异反模式识别的“择近原则”和聚类分析思想构造集对分析动态模型，模型精度较高，验证误差均小于0.3%。并对武汉市2005年～2020年总生态足迹发展趋势进行了预测。研究结果表明，2005年～2020年总生态足迹将由1 784.662×10⁴hm²增长到2 781.388×10⁴hm²，呈现出低于GDP、高于能源利用率增长速率的趋势，生态环境将进一步恶化，对此就武汉市生态系统的发展提出了对策与建议。最后，指出SPA动态模型对城市生态系统中生态足迹动态化方法的修正具有理论和实际意义。     

句型转换的机器翻译理论模型与一些处理方法

自动分词和译文生成处理是混合式汉英机器翻译的两个重要阶段。本文主要工作有：第一，讨论了机器翻译的理论模型；第二，给出了一个自动分词算法，提出了一个初步消歧方法；第三，建立汉英机器翻译的时态转换及相关匹配规则。     

隧道锚碇围岩稳定分析及破坏模式研究

锚碇围岩稳定性及破坏模式研究是确定系统极限承载力的基础。基于现场地质资料的数值仿真计算与现场缩尺模型试验对比分析,被认为是一种比较理想的研究思路。通过FLAC3D计算发现,在设计荷载下,围岩的应力场和位移场具有明显的分区特征,在锚体空腔和结构拐角处常出现应力集中和大变形区,系统整体未形成连贯的破坏区,出现的局部破损区主要集中在锚体后部右上角等5个部位。超载数值试验发现,破坏并不是简单的沿锚体和岩体的边界发生滑移,而是带动周边岩体发生倒塞型的整体拉剪复合破坏。现场模型试验结果与数值计算结果吻合较好。施工及运营过程中应对易破坏区进行重点加固处理。     

日美风险投资模式的比较分析

通过比较分析,日美风险投资模式在资本供给主体、组织形式、运作方式及政府充当的角色等方面存在着明显的差异。我国风险投资的发展,不能照搬外国模式,在学习和借鉴的同时,必须从我国的实际情况出发,构建有中国特色的动态风险投资模式。     

智力资本及其测度研究

在知识经济条件下,企业智力资本已成为企业最重要的资源。在剖析智力资本概念和内涵的基础上,结合企业智力资本管理模型,提出了基于价值形式的整体存量测度、非价值形式的分量测试以及存量对比与转换式的流量测度的智力资本测度思路和框架。     

结构导向组织创新、技术创新与组织绩效的牵引效应

构建结构导向组织创新、技术创新与组织绩效的牵引效应模型,以结构导向组织创新为潜在自变量,以技术创新为潜在调解变量,以组织绩效为潜在因变量,对347家高技术制造企业进行问卷调研及深度访谈,应用结构方程模型(SEM)分析结构导向组织创新、技术创新与组织绩效的牵引效应.研究表明,结构导向组织创新对组织绩效没有显著的直接影响,但会直接拉动企业技术创新活动的开展和实施效果,并以技术创新为媒介对组织绩效产生显著的影响,由此证明结构导向组织创新、技术创新与组织绩效三者之间存在牵引效应.     

Dependency structure language model for topic detection and tracking

In this paper, we propose a new language model, namely, a dependency structure language model, for topic detection and tracking (TDT) to compensate for weakness of unigram and bigram language models. The dependency structure language model is based on the Chow expansion theory and the dependency parse tree generated by a linguistic parser. So, long-distance dependencies can be naturally captured by the dependency structure language model. We carried out extensive experiments to verify the proposed model on topic tracking and link detection in TDT. In both cases, the dependency structure language models perform better than strong baseline approaches.     

Parsimonious translation models for information retrieval

In the KL divergence framework, the extended language modeling approach has a critical problem of estimating a query model, which is the probabilistic model that encodes the user’s information need. For query expansion in initial retrieval, the translation model had been proposed to involve term co-occurrence statistics. However, the translation model was difficult to apply, because the term co-occurrence statistics must be constructed in the offline time. Especially in a large collection, constructing such a large matrix of term co-occurrences statistics prohibitively increases time and space complexity. In addition, reliable retrieval performance cannot be guaranteed because the translation model may comprise noisy non-topical terms in documents. To resolve these problems, this paper investigates an effective method to construct co-occurrence statistics and eliminate noisy terms by employing a parsimonious translation model. The parsimonious translation model is a compact version of a translation model that can reduce the number of terms containing non-zero probabilities by eliminating non-topical terms in documents. Through experimentation on seven different test collections, we show that the query model estimated from the parsimonious translation model significantly outperforms not only the baseline language modeling, but also the non-parsimonious models.     

An empirical study of query expansion and cluster-based retrieval in language modeling approach

The term mismatch problem in information retrieval is a critical problem, and several techniques have been developed, such as query expansion, cluster-based retrieval and dimensionality reduction to resolve this issue. Of these techniques, this paper performs an empirical study on query expansion and cluster-based retrieval. We examine the effect of using parsimony in query expansion and the effect of clustering algorithms in cluster-based retrieval. In addition, query expansion and cluster-based retrieval are compared, and their combinations are evaluated in terms of retrieval performance by performing experimentations on seven test collections of NTCIR and TREC.     

基于虚拟环境的黄河仿真系统构建

虚拟现实的产生和发展无疑为加强地理科学研究提供了强大的手段和方法上的支持.本文从虚拟环境的角度出发,给出了一个黄河仿真系统的建设方案,它包括数据源、三维仿真地形库、三雏仿真模型库、三维仿真虚拟实现四大模块.然后详细探讨了黄河仿真系统的关键技术: ①通过对三维图形开发工具OpenGL的原理、实现功能等的分析,提出了在黄河仿真系统建设中OpenGL技术的具体应用实现方法,实现了实时动态漫游; ②基于MultiGen Creator的真实感三维模型建设; ③利用OpenGL和MO来实现三维场景与二维电子地图的互响应;这充分发挥了三维场景与二维电子地图各自的优势,有机地结合了三维虚拟场景的直观性、现实性、局部性和二维电子地图的宏观性、整体性、简洁性的优点,同时又克服了三维虚拟场景漫游的方向迷失感和二维电子地图的抽象多义性.