The operational semantics of user-defined relationships in object oriented database systems

In semantic data models, abstract relationship (e.g. generalization, aggregation, etc.) semantics are defined, specifying how insertion, deletion and modification operations made at a higher level of abstraction can affect the objects abstracted over and vice versa. These semantics, also known as structural constraints, are expressed through so-called update rules. This perspective has been somewhat lost in most object-oriented systems, where user-defined relationships are supported as simple pointers and their semantics are embedded, distributed and replicated within the operations accessing these pointers. This paper inherits and extends the treatment of relationships found in semantic data models to behavioural object-oriented models by presenting an approach to uniformly capture the update rules for user-defined relationships. The stress is not on supporting relationships as first-class objects, but on describing their update rules (or operational semantics) through a set of constructors namely, reaction, anticipation, delegation and exception. The approach has been borne out by an implementation in an active object-oriented database system.     

Nonlinear black-box modeling in system identification: a unified overview

A nonlinear black-box structure for a dynamical system is a model structure that is prepared to describe virtually any nonlinear dynamics. There has been considerable recent interest in this area, with structures based on neural networks, radial basis networks, wavelet networks and hinging hyperplanes, as well as wavelet-transform-based methods and models based on fuzzy sets and fuzzy rules. This paper describes all these approaches in a common framework, from a user's perspective. It focuses on what are the common features in the different approaches, the choices that have to be made and what considerations are relevant for a successful system-identification application of these techniques. It is pointed out that the nonlinear structures can be seen as a concatenation of a mapping form observed data to a regression vector and a nonlinear mapping from the regressor space to the output space. These mappings are discussed separately. The latter mapping is usually formed as a basis function expansion. The basis functions are typically formed from one simple scalar function, which is modified in terms of scale and location. The expansion from the scalar argument to the regressor space is achieved by a radial- or a ridge-type approach. Basic techniques for estimating the parameters in the structures are criterion minimization, as well as two-step procedures, where first the relevant basis functions are determined, using data, and then a linear least-squares step to determine the coordinates of the function approximation. A particular problem is to deal with the large number of potentially necessary parameters. This is handled by making the number of ‘used’ parameters considerably less than the number of ‘offered’ parameters, by regularization, shrinking, pruning or regressor selection.     

计算机生成兵力中的人工智能技术

开发CGF的难点和重点在于CGF实体行为的生成,尤其是人类智能行为的实现。人类行为建模最重要的三个方面是知识获取、知识表示和决策机制,都与人工智能技术相关。该文主要介绍人类行为描述的知识表示和知识获取问题,讨论了人工智能技术在这两个方面的应用,并对将来的研究工作做了一个简单的展望。     

储层地质模型与油藏模拟模型之间的桥梁——一种有效的模型粗化方法

针对油田储层地质模型向油藏模拟模型转化中粗化软件存在的问题 ,提出了一种实用的网格粗化方法 ,并编制了模型粗化程序 ,还给出了检验粗化结果的 5个要点。应用效果表明 ,该粗化方法是有效的 ,它较好地解决了地质模型与油藏模型之间的转化问题     

Automated Support for Building and Extending Expert Models

Building a knowledge-based system is like developing a scientific theory. Although a knowledge base does not constitute a theory of some natural phenomenon, it does represent a theory of how a class of professionals approaches an application task. As when scientists develop a natural theory, builders of expert systems first must formulate a model of the behavior that they wish to understand and then must corroborate and extend that model with the aid of specific examples. Thus there are two interrelated phases of knowledge-base construction: (1) model building and (2) model extension. Computer-based tools can assist developers with both phases of the knowledge-acquisition process. Workers in the area of knowledge acquisition have developed computer-based tools that emphasize either the building of new models or the extension of existing models. The PROTÉGÉ knowledge-acquisition system addresses these two activities individually and facilitates the construction of expert systems when the same general model can be applied to a variety of application tasks.     

非线性动态系统“黑箱”建模方法的研究

本文研究弱非线性动态系统“黑箱”建模的理论和方法，并简要给出根据此方法建模的结果。     

万顷沙西十三涌油轮码头模型试验研究

华隆公司拟在万顷沙西十二涌与十三涌之间兴十三涌３０００Ｔ级油轮港口码头。本文分析了该河段水文泥沙的特性、河道演变趋势及河段稳定性，通过物理模型试验研究及对航道、港池的回淤计算分析，预测工程建成后引起局部水流流态的变化，对水道泄洪、潮排、潮灌的影响，以及港池、航道建成后的泥沙淤积情况。     

用面向对象编程实现问题求解自动化

本文从面向对象方法基本原理和面向对象编程的技术特征出发，阐明所建应用软件系统中的对象，类及相应类层次结构和类组合结构，使系统具有很强的表现真空世界复杂系统结构的能力，系统通过消息传递在程序执行中实现对操作的调用机制，使之在面向用户问题选择和执行求解策略方面有很强的适应性，这一点对于强调人－机交互和解题协作的智能决策支持系统设计至关重要，文章给出了用Ｃ＋＋实现的模型对象系统及消息传递机制。     

基于多模型半参数非线性回归模型的外弹道节省参数估计

双星定位系统的应用是外弹道估计中的一种发展趋势。文章给出基于双星、光雷的联合测量模型,建立基于半参数回归的外弹道节省参数估计模型;给出基于半参数回归的外弹道节省参数估计算法及计算步骤,并从理论上分析了基于半参数回归的外弹道节省参数估计算法能有效地消除非线性因素对参数估计性能的影响,其估计精度优于经典的节省参数建模方法,并通过仿真得到：该算法确实有效。     

仿真系统互操作性研究

如何提升系统的互操作性是当前仿真领域需要着力解决的问题,而理解互操作问题产生的根源则是提升互操作性的前提。从互操作性的概念分析人手,剖析了仿真系统互操作问题产生的原因,将之概括为组织、抽象和实现三个层面,并提出了相应的解决框架。框架通过建立概念模型库和平台无关模型库解决抽象层面的问题,利用模型实现的自动化和服务化解决实现层面的问题,可以作为领域内解决互操作问题的借鉴。最后提出了使用对比法和测试法评估系统互操作性的思路。