船舶抗沉辅助决策系统的研究与设计

抗沉辅助决策系统是船舶常规和紧急状态下进行损管行动的关键性依据。目前抗沉计算分析系统,可对船舶基础状态、浮稳性等信息进行管理,并进行仿真和辅助决策,但大多存在算法效率低,决策生成速度和精度不足、人机交互接口脱离实际等问题。本文从船舶抗沉操作的实际执行过程出发,制定抗沉算法,根据实时装载和破损情况,对液舱采用注入水或排水的损管操作,生成调整措施,使船舶恢复良好的浮态与稳性。系统基于面向对象过程控制平台设计和实现,仿真结果验证了系统的有效性和高效性。     

基于时空数据库的船舶损管系统研究

在船舶管理系统设计问题的研究中,由于船舶系统的日益复杂化,传统的损管信息管理方式难以准确掌控全船情况,导致损管资源调度低效.针对上述问题,将时空数据库技术与时空可视化技术引入船舶损管信息管理中,提出了基于二元组的适应于动态路网的损管资源调度算法,通过对船舶系统进行时空建模,采用二元组方式描述路径权值,并依据路径必须经过关键节点集合的特点,对路网进行剪枝,降低路径规划中节点访问数量.仿真结果表明,与Dijkstra算法相比,改进算法时间性能平均提高35％,有效提升了损管资源调度效率,为船舶系统安全性提供了保障.     

基于场景及规则获取模板的知识获取方法

产生式规则作为知识库系统进行推理的常用的、可读性好的知识表示形式,在构建知识库系统时有极大的优越性.提出一种基于场景及规则获取模板的知识获取方法,并以某高分子复合材料的加工专家为知识获取对象.该方法通过分析、记录领域专家进行设计的过程、解决问题的过程和动作,将领域问题按层次细化为一系列子问题,并在子问题场景下结合场景模型及知识获取模板来获取规则性知识.采用该方法可以辅助领域专家在明晰领域知识结构的基础上,逐步挖掘领域中细粒度的规则性知识.     

基于Prompt的两阶段澄清问题生成方法

在自然语言相关系统中,当用户输入存在歧义时,生成澄清问题询问用户有助于系统理解用户需求;基于Prompt的方法可以更好地挖掘预训练语言模型的潜在知识,但往往需要手动设计模板,限制其生成澄清问题的多样性。为解决这一问题,提出了TSCQG（two-stage clarification question generation）方法。首先,在动态Prompt模板生成阶段,利用歧义上下文和预训练语言模型生成动态的Prompt模板;然后在缺失信息生成阶段,将Prompt模板与外部知识相结合,充分利用预训练语言模型的生成能力生成相应的缺失信息。实验结果表明,在CLAQUA数据集的多轮对话情况中,BLEU值和ROUGE-L值分别达到了58.31和84.33,在ClariQ-FKw数据集上,BLEU值和ROUGE-L值分别达到了31.18和58.86。实验结果证明了TSCQG方法在澄清问题生成任务上的有效性。     

一个源代码自动生成工具的设计与实现

讨论了一个源代码自动生成工具的设计思想和实现技术,关键性技术是基于标记语言XML的模板语言.它将被应用到嵌入式组件中去,通过对已有模板的配置来生成源代码.     

基于多Agent的智能导学系统的研究与设计

智能导学系统是针对CAI系统的不足而提出的能够基于领域知识和学生模型进行决策、指导的教学系统。多Agent技术为智能导学系统的设计与实现提供了解决方案。本文主要讨论了基于多Agent技术开发的智能导学系统的功能设计以及数据库系统设计。     

基于XML的构件自动组装系统的设计与实现

该文利用基于XML和Java的程序自动生成技术给出了一个构件组装系统的设计,提出了SAML应用模板语言的定义。连接器利用了消息总线的思想,通过共享消息资源的方式连接构件,从而将构件之间的连接关系解耦。在自动生成应用系统时对SAML模板文件进行分析、转换,自动生成消息分发器和最终可执行应用程序,并结合B2C电子购物领域给出一个原型实现。该设计方法为实现自动的构件组装技术提出了一种解决方案。     

卫星星座健康状态管理文档的自动生成方法

针对卫星星座健康状态管理文档涉及多项遥测参数的查询和计算、文档格式要求严格、编制工作量巨大、人工耗时较长的问题,提出了一种卫星星座健康状态管理文档自动生成方法.通过对文档中所含的基本数据类型进行归类分析,制定配置文件存储规则,对文档模板进行自定义设置,并应用文档自动生成算法,利用文档模板及相关参数生成数据汇总文档.该方法能够实现文档编制过程中的知识复用和通用内容生成,建立规范有效的文档编制流程.     

一种基于与或图表示的多风格肖像画自动生成方法

提出了一种基于与或图表示的多风格肖像画自动生成方法.与或图表示是一种分层次的产生式模型,能够分离肖像画的结构和风格并解释其多样性.采用这种模型,该方法能够从一幅正面的人脸图像自动地产生出一系列不同风格的肖像画.该方法将肖像画分解成各个部分,每一部分都对应许多子模板,这些子模板作为肖像画与或图中的叶子结点.而肖像画与或图就像一个"母模板"能够产生出大量的由子模板组合而成有效的新肖像画.该方法受益于多个不同风格的模板库,改变模板库的风格就能方便地更改生成肖像画的风格.文中所提供的例子表明了该方法的有效性.     

轨道交通联锁领域特定语言的形式化

作为轨道交通系统的核心子系统之一，对联锁系统进行形式化建模与分析，是保证其安全性的重要手段.形式化建模需要领域知识和形式化知识的结合，由于形式化知识难以掌握，领域专家在建模整个过程中都需要形式化专家的帮助.为了解决这个问题，针对联锁系统的故障随机性、行为实时性、构件可重用的特点，提出设计联锁领域特定语言IS-SDL描述具体的联锁系统的参数，并基于随机混成自动机模板自动生成联锁系统的形式化模型，以进一步在此基础上进行安全分析.首先对联锁系统模型进行分析，根据不同案例设计其领域特定语言；其次，确定联锁系统的系统模型的模板，包括环境构件模板和控制器模板，并举例抽取其随机混成自动机模板；在模板基础上定义系统模型生成过程，让领域专家可以通过领域特定语言，输入参数自动生成具体的随机混成自动机系统模型；最后以某站联锁系统为例，展示了基于模板的具体系统模型的生成过程，并通过基于系统模型的事故预测分析，证明了该方法的可行性与有效性.     

Representing complex knowledge in an intelligent machine tutor

Knowledge representation remains a serious issue for researchers of intelligent tutoring systems. Two areas of knowledge representation that are particularly difficult are domain and teaching knowledge. This article discusses and gives example solutions to these knowledge engineering issues and also addresses issues that relate to up-scaling existing intelligent tutoring technology to practical levels so that tutoring systems can be brought into the real world.     

基于概念网络的领域知识组织及应用

着眼于智能教学系统领域知识库的建立，引入了一种新的知识表达工具——概念网络（Connet），并结合军事后勤保障计算教学系统的领域知识库和知识导航系统的建立，通过实例就如何使用这种表达工具进行知识组织和管理进行了介绍。     

基于智能技术的远程教育答疑系统研究

网上答疑系统是现代远程教育系统中不可缺少的一部分,然而当前的答疑系统只是根据用户的输入对题库中的问题进行简单的关键词匹配,查询精度和用户界面满足不了用户的需求。针对以上缺点,本文给出一个应用语义网络原理构筑起来的智能答疑系统。文章分析了建立智能答疑系统的必要性,由此提出了一个基于限定领域的智能答疑系统模型及其技术路线,并以两门大学计算机课程作为知识库来源,实现了系统的功能。试验结果表明,本文所提出的方法有效地提高了查询精度,用户界面友好方便。     

基于概念网络的智能教学系统--OMT

从知识管理的角度出发，利用知识表达工具概念网络（Connet）为智能教学系统OMT（Olympic Math Tutoring）构造知识模型，以“知识树”的形式呈现领域知识的层次和逻辑关系。同时使用覆盖知识树的概率网络建立学生模型，结合习题参数的设计达到解释学生学习行为、为学生提供个性化教学的目的。     

Curriculum knowledge representation and manipulation inknowledge-based tutoring systems

A knowledge-based tutoring system (KBTS) is a computer-based instructional system that uses artificial intelligence techniques to help people learn some subjects. We found that the knowledge communication process involving a KBTS and a human student can be decomposed into a series of communication cycles, where each cycle concentrates on one topic and contains four major phases: planning, discussing, evaluating and remedying. The major contributions of this work are the development of a generic architecture for supporting the knowledge communication between a KBTS and a student, and a graphical notation and schema for supporting the curriculum knowledge representation and manipulation during the planning phase of a tutoring process. The curriculum knowledge about a course can help a tutoring system determine the sequences in which the topics will be discussed with the students effectively and diagnose the students' mistakes. The curriculum knowledge base contains the goal structure of the course, prerequisite relations, and multiple ways of organizing topics, among others. As an example, we focus on developing SQL-TUTOR, a KBTS for the domain of SQL programming. This system has features such as an efficient control mechanism, explicit curriculum knowledge representation, and individualized private tutoring. For allowing the students relative freedom to decide how to study the domain knowledge about a subject, the system provides the students with a group of operators to hand-tailor the learning schedules according to their special backgrounds, requests, and interests     

Education, training and knowledge base design

Abstract: Knowledge based systems offer considerable potential for the creation of new learning environments. In education such environments can be used with the mediation of a teacher and limits to the interpretation of the knowledge do not necessarily present problems. Intelligent tutoring systems cannot rely on human mediation and all interpretation of learner understanding is restricted to semantics of the knowledge representation. Thus the choice of representation is fundamental to the design of an intelligent tutoring system. Experience from an engineering context suggests that the success of a few intelligent tutoring systems depends on the formal nature of the topics considered. Typical topics for education and training require the integration of a formal understanding with an informal interpretation of considerable complexity. A new approach to the use of knowledge based systems, firmly centred on experience of applications actively used in education and/or training, will be required to solve this problem.     

Incorporating tutoring principles into interactive knowledge acquisition

This paper argues that interactive knowledge acquisition systems would benefit from a tighter and more thorough incorporation of tutoring and learning principles. Current acquisition systems learn from users in a passive manner, and could instead be designed to incorporate the proactive capabilities that one expects of a good student. We first describe our analysis of the literature on teacher–student interaction and present a compilation of tutoring and learning principles that are relevant to interactive knowledge acquisition systems. We then point out what tutoring and learning principles have been used to date in the acquisition literature, though unintentionally and implicitly, and discuss how a more thorough and explicit representation of these principles would help improve how computers learn from users. We present our design and an initial implementation of an acquisition dialogue system called SLICK that represents acquisition principles and goals explicitly and declaratively, making the system actively reason about various acquisition tasks and generate its interactions dynamically. Finally, we discuss promising directions in designing acquisition systems by structuring interactions with users according to tutoring and learning principles.     

Ontological Engineering and Mathematical Knowledge Management: A Formalization of Projective Geometry

The work presented in this paper deals with the formalization of the ontology underlying projective geometry. This formalization is done by using the conceptual graph model which has been defined in the Artificial Intelligence community. Through this experiment, we endeavour to show that applying knowledge representation techniques to mathematical fields is a relevant way to improve the reliability and efficiency of tools dedicated to mathematical knowledge management. Our proposal is based on the construction of knowledge bases (defined according to ontologies) which must be considered as the core of any mathematical knowledge management tool such as mathematical search engines on the web, mathematical intelligent tutoring systems, mathematical theorem provers, etc. This paper also aims at highlighting the contributions provided by ontological engineering when dealing with mathematical knowledge management.     

以知识点为中心的智能教学系统的研究与构建

在深入研究智能教学系统知识表示方法的基础上,提出了一个以知识点为中心的智能教学系统构建方案,采用知识点作为教学资源的组成单位,通过知识点间的联系来构建知识体系,并结合Web挖掘、人工智能、模糊理论等技术,实现网络教学的智能教学策略。