基于Prolog的专家系统研究与应用

随着计算机与网络通信技术的迅猛发展,特别是互联网的大规模普及,围绕人工智能与专家系统的研究和应用开发也迎来一个蓬勃发展的新时期.Prolog语言是人工智能与专家系统领域最著名的逻辑程序设计语言.本文基于Prolog平台上,探讨了专家系统建造的原理和应用.     

基于Prolog的专家系统研究与应用

随着计算机与网络通信技术的迅猛发展,特别是互联网的大规模普及,围绕人工智能与专家系统的研究和应用开发也迎来一个蓬勃发展的新时期。Prolog语言是人工智能与专家系统领域最著名的逻辑程序设计语言。本文基于Prolog平台上,探讨了专家系统建造的原理和应用。     

Visual Prolog语言在测试设备故障诊断专家系统中的应用

Visual Prolog语言是人工智能与专家系统领域最著名的逻辑程序设计语言,适合表达人的思维和推理规则,能够方便地实现模式匹配、回溯、事实数据库和谓词等功能;针对导弹测试设备结构复杂、故障隔离与定位困难等情况,充分利用Visual Prolog语言在专家系统知识表示及逻辑推理过程中的优点,建立了一个基于规则的导弹测试设备故障诊断专家系统;通过应用表明Visual Prolog语言十分适合构建此类专家系统,并具有良好的开发应用前景.     

基于规则的鸟类识别专家系统的设计与实现

本文首先介绍人工智能领域中专家系统的概念及特点,以及基于规则的专家系统的模型与结构,其次以建立一个鸟奚识别专家系统为例来说明基于规则的专家系统的详细设计与实现。旨在说明构造专家系统的步骤与方法,软件设计采用人工智能语言Prolog编程实现。     

Prolog在开发智能教学系统中的应用

近几年来,随着计算机与网络技术的迅猛发展,特别是因特网的大规模普及,人工智能的研究活跃起来,并正向更广阔的领域发展。VisualProlog是国际上已经广泛流行的功能强大的通用智能化应用集成开发环境,引进Prolog,对于开发智能应用系统十分必要。论文主要分析了Prolog语言的特点及基本结构,并分析了智能教学系统的工作原理,在此基础上给出了采用Prolog语言实现的一个简单的学生模糊综合评价的专家系统。其中对学生的评估指标分为五级,相应地规定了五条评估规则。     

基于Prolog语言的装备维修决策专家系统设计与开发

采用Prolog智能语言对装备维修决策专家系统进行了设计与开发。从维修知识和推理能力两方面研究了装备维修专家的基本特点;分析了基于Prolog的专家系统的基本语法、推理方式及其在装备维修中的应用方式;设计并开发了装备维修决策专家系统的元知识库、关联知识库和应用知识库;最后采用Visual Prolog和VC++混合编程方式开发了某装备维修决策专家系统。     

人工智能语言LISP与Prolog之争

围绕日本第五代机计划所作的宣传已使系统开发人员警觉到人工智能的长远潜力。美国两个主要开发语言:LISP 与 Prolog 的支持者展开了激烈的论战。所争论的问题不在于九十年代计算机将使用哪种语言,而在于哪种语言对开发流行的人工智能软件产品(如专家系统)有更大的潜力。     

Prolog语言的特点及其仿真应用

Prolog语言是人工智能语言之一。本文讨论了Prolog语言的特点及其仿真适应性,分析了Prolog语言用于仿真时的长处和短处。     

人工智能语言——PROLOG

Prolog是人工智能语言的一个典型代表。本文简要阐述了人工智能语言及其特点,并通过实例介绍了Prolog语言及其基本结构。     

一个面向向量机的Prolog系统—VProlog

1.引言 近年来,小型化的向量巨型机已逐渐商品化,与向量巨型机相比,小型化的向量巨型机的性能价格比大为提高,其价格大大下降,但这种机器具有庞大的内存容量和很高的处理速度,因此,预计将受到广大用户的欢迎而得到普及,考虑到充分利用已有的四代机中很成功的向量巨型机的资源来改进Prolog语言的执行效率,以满足人工智能、专家系统等的应用需要,我们研究了如何利用向量机及Prolog本身所固有的并行、并发性来有效地实现一个Prolog系统——VProlog系统。     

基于逻辑推理的转子故障诊断专家系统

采用人工智能专家系统计算机技术模拟故障诊断领域专家的推理思维方式,对机械设备发生的故障实现迅速准确的诊断,同时缩短故障停机时间具有重大意义。本文应用Visual prolog语言,构造了转子系统故障诊断专家系统,提出了一阶谓词逻辑子句表达知识的方法,建立了专家知识库。系统的推理机采用深度优先的推理策略。应用表明系统有效完成旋转机械常出现的十多种故障的诊断,并运行可靠。     

An expert system for experimental design in off-line quality control

Abstract: Robust design is an efficient method for designing high quality products at low cost. The method examines the effect of a large number of design factors on the variability of a product's response due to various sources of disturbance. This effect can be observed efficiently by studying a large number of variables simultaneously through balanced, orthogonal array experiments, and by analyzing the resulting data using variance decomposition methods. In this paper we describe an expert system prototype for designing efficient experiments. Given the information on various parameters and their levels, the system designs an experiment using orthogonal arrays. This expert system is implemented in Prolog, which is a logic programming language for artificial intelligence research and expert systems development. The system was implemented under the P-Shell knowledge programming environment on UNIX.     

UCB策略在Prolog中的应用

Prolog(Programming in Logic)程序语言是一种逻辑程序设计语言.它是在逻辑学理论基础上建立起来的并广泛应用在人工智能研究中.这几十年已经出现了各具特色的Prolog编译器,而且各种编译器也都很成功.虽然在现阶段已经出现了各种版本Prolog编译器,但是Prolog编译器的发展空间还是很大.本文先通过现代Prolog编译器的不足,介绍了新Prolog编译器的特点,然后简单叙述了Prolog编译器词法分析和语法分析的过程,最后介绍了UCB策略.     

Low cost control education software for MS-DOS PCs

This paper describes a low cost learning environment for control and artificial intelligence techniques. It is shown how public domain and shareware software can be combined with university products to provide a learning basis of considerable power and versatility. The control part contains programs for matrix calculations and simulations as well as training programs for specific tasks. The artificial intelligence part contains Prolog, Lisp (XLisp), several small expert system shells and simulators for discrete events systems.     

Visual Prolog 6面向对象技术与应用

Visual Prolog是国际上广泛流行的功能强大的通用智能化应用集成开发环境,它是基于Prolog的强类型的面向对象程序设计语言.文章讨论了Visual Prolog 6的面向对象技术及其在专家系统设计中的应用,实现了一个称为“失踪儿童协寻专家系统”的示例,经运行测试,效果良好.     

An application of artificial intelligence to object-orientedperformance design for real-time systems

The paper describes an application of artificial intelligence technology to the implementation of a rapid prototyping method in object-oriented performance design (OOPD) for real-time systems. OOPD consists of two prototyping phases for real-time systems. Each of these phases consists of three steps: prototype construction, prototype execution, and prototype evaluation. We present artificial intelligence based methods and tools to be applied to the individual steps. In the prototype construction step, a rapid construction mechanism using reusable software components is implemented based on planning. In the prototype execution step, a hybrid inference mechanism is used to execute the constructed prototype described in declarative knowledge representation. MENDEL, which is a Prolog based concurrent object-oriented language, can be used as a prototype construction tool and a prototype execution tool. In the prototype evaluation step, an expert system which is based on qualitative reasoning is implemented to detect and diagnose bottlenecks and generate an improvement plan for them     

基于Visual Prolog 6.3内核的专家系统实现

针对目前构建专家系统开发环境的局限性造成开发周期长的问题,提出了利用传统语言调用逻辑程序设计语言的动态链接库构建专家系统的方法,通过两类语言优势互补,实现高效开发专家系统。详细论述了Visual Prolog 6.3动态链接库的生成过程、调用方式、调用约定以及编码转换,并介绍了利用VB.net如何调用Visual Prolog 6.3生成的动态链接库构建专家系统。通过实例验证了该方法的可行性,并具有良好的应用前景。     

Prolog versus Kee — A case study

The selection of the software development tool for the development of an expert system is a difficult and often disputed decision. This paper describes a comparison of a knowledge engineering tool, Kee, and a general purpose language, Prolog, on concrete and real life example from AGATHA, an electronic circuit board diagnosis expert system.Prolog is a high-level programming language with flexible and powerful inference mechanisms. Kee is a big tool that supports a frame-based knowledge representation, an object-oriented programming style and a built-in rule system. It also offers a window environment suitable for rapid development of user-interface prototypes.Prolog's representation is more succinct, implicit and uses problem specific predicates and therefore leaves more room for personal programming styles. Kee is more verbose, explicit and uses standard templates. The maintainability of a Prolog implementation relies heavily on good documentation. In Kee, the unavoidable ‘escapes to Lisp’ require a maintainer to be fluent in Kee and Lisp.Both Prolog and Kee require a considerable investment in learning time.