完全析取范式群判定SHOIN(D)-可满足性

针对非循环概念提出了一种对SHOIN(D)-概念可满足性进行判断的方法——CDNF(complete disjunctive normal form)算法.该算法通过把非循环定义的概念描述本身构建成分层次的析取范式群,并通过子句重用技术阻止无谓的子概念扩展,这样的析取范式群具有可满足性自明性,从而可以实现对SHOIN(D)-概念可满足性的直接判断.该算法基本上消除了判断过程中描述重复的现象,从而在空间、时间性能上都比Tableau算法有更好的表现.     

基于物元理论的任意功能树相似扩展方法

功能模型是概念设计的核心处理对象,功能树是一种典型的、应用广泛的 功能模型。使用现有相似度计算方法计算任意功能树的相似度存在困难。因此,基于布尔代 数提出了析取范式树的概念,以及两种求解析取范式树的方法,并描述了任意功能树的物元 相似度计算方法。拓展了功能树相似扩展方法的应用范围,扩大了设计解空间,增加了获得 创新解的可能性,最后给出实例验证了方法的有效性。     

从合取范式到析取范式的转换研究

为了解决粗糙集分辨函数的计算、概念格中内涵缩减的计算、逻辑程序设计的规则简化等问题,抽象出了从合取范式到析取范式转换这一核心问题。提出了利用极小覆盖来实现从合取范式到析取范式的转换,给出了一个增量式的算法。为了扩大范式转换的使用范围,定义了伪合取范式,并给出伪合取范式到析取范式的转换方法。     

基于连续过程特性的炼油生产调度优化研究

针对炼油生产调度问题,基于连续过程特性建立了广义析取规划调度模型。提出了连续性、长期性等连续过程特性定义及其性能指标,基于析取范式和逻辑命题对调度初期、中期和末期的连续过程特性进行了描述,并对连续过程特性性能进行了量化表达和评价,以实现生产利润和连续过程特性性能的综合利益最大化。以某炼油过程生产调度为例,对比有无连续过程特性表达的优化调度仿真结果表明：基于连续过程特性调度模型的调度方案能够提高连续过程特性性能,且更可行、实用,验证了模型的可行性和有效性。     

Top-Down Query Processing in First-Order Deductive Databases under the DWFS

A top-down query-processing method for first-order deductive databases under the disjunctive well-founded semantics (DWFS) is presented. The method is based on a characterization of the DWFS in terms of the Gelfond–Lifschitz transformation and employs a hyperresolution-like operator and quasi-cyclic trees to handle minimal model processing. The method is correct and complete and can be guaranteed to terminate given certain mild constraints on the format of database rules. The efficiency of the method is enhanced by the fact that large parts of the search tree are naturally grounded, even for first-order queries and databases. In the case of a grounded yes/no answer, the search tree becomes nongrounded only if processing enters the definite part of the database. For finite propositional databases the method runs in polynomial space. Efficiency may be enhanced by the application of partial compilation.     

An alternative approach to the semantics of disjunctive logic programs and deductive databases

In this paper, we study a new semantics of logic programming and deductive databases. Thepossible model semantics is introduced as a declarative semantics of disjunctive logic programs. The possible model semantics is an alternative theoretical framework to the classical minimal model semantics and provides a flexible inference mechanism for inferring negation in disjunctive logic programs. We also present a proof procedure for the possible model semantics and show that the possible model semantics has an advantage from the computational complexity point of view.This is a revised and extended version of the paper [36] which was presented at the Tenth International Conference on Logic Programming, Budapest, 21–25 June 1993.     

COMPUTING PERFECT AND STABLE MODELS USING ORDERED MODEL TREES

Ordered model trees were introduced as a normal form for disjunctive deductive databases. They were also used to facilitate the computation of minimal models for disjunctive theories by exploiting the order imposed on the Herbrand base of the theory. In this work we show how the order on the Herbrand base can be used to compute perfect models of a disjunctive stratified finite theory. We are able to compute the stable models of a general finite theory by combining the order on the elements of the Herbrand base with previous results that had shown that the stable models of a theory T can be computed as the perfect models of a corresponding disjunctive theory ɛ T resulting from applying the so called evidential transformation to T. While other methods consider many models that are rejected at the end, the use of atom ordering allows us to guarantee that every model generated belongs to the class of models being computed. As for negation-free databases, the ordered tree serves as the canonical representation of the database.     

网络安全系统中的快速规则匹配

随着网络攻击的增多,各类安全系统被广泛应用,其关键和核心是规则匹配.加速规则匹配可以提高系统性能,使其适应更高速网络和更严格环境.介绍和分析了现有的两种主要规则匹配算法:布尔表达式树和有向无环控制流图,提出了一种快速规则匹配算法.该算法先对有向无环控制流图进行等价变换,再在此基础上进行概率优化和改进,通过调整规则内部的逻辑表示结构,使得规则的结构转换速度和计算速度都得到明显的提高.经过测试比较,该算法能有效缩短匹配时间,改善系统性能.     

Rough Set 规则自动生成的关键算法改进

基于RoughSet理论,研究从Skrowon分辨矩阵到规则自动生成过程中的关键算法的改进问题。提出由分辨矩阵到合取项矩阵的计算方法,建立了从属性约简的合取项矩阵到析取项矩阵转换的数学模型,基于数学模型,提出直接搜索的转换方法。同时,提出了属性值约简的改进方法,使得改进后的算法从总体上节省了运算空间,降低了算法的时间复杂性,提高了规则生成的效率。最后通过UCI数据库的实例验证了改进算法的有效性。     

A Benders decomposition framework for the optimization of disjunctive superstructures with ordered discrete decisions

This study introduces the logic-based discrete-Benders decomposition (LD-BD) for Generalized Disjunctive Programming (GDP) superstructure problems with ordered Boolean variables. The key idea is to obtain Benders cuts that use neighborhood information of a reformulated version of Boolean variables. These Benders cuts are iteratively refined, which guarantees convergence to a local optimum. A mathematical case study, the optimization of a network with Continuous Stirred-Tank Reactors (CSTRs) in series, and a large-scale problem involving the design of a distillation column are considered to demonstrate the features of LD-BD. The results from these case studies have shown that the LD-BD method exhibited good performance by finding attractive locally optimal solutions relative to existing logic-based solvers for GDP problems. Based on these tests, the LD-BD method is a promising strategy to solve optimal synthesis problems with ordered discrete decisions emerging in chemical engineering applications.