基于偏序关系的演化算法

在演化算法中引起卢偏序关系（称为优适应关系）,把评估个体适应性能的机制从适应值函数一般化为优适应关系,在此基础上定义演化算法求解的问题一般形式并修正了演化算法的基本结构,从而使演化算法概念更清晰,在理论上澄清了一些演化算法概念上的分歧,为演化算法应用于更广泛的领域提供理论指导。     

启发式全局偏序挖掘算法

偏序模型能直观反映序列数据信息,全局偏序模型能进一步从整体上更加准确反映序列的全局信息,方便用户的理解.本文对全局偏序模型的构建方法进行研究,针对基于遍历搜索构建模型所造成的效率较低,不宜扩展的问题,提出基于启发式搜索的全局模型构造改进算法.在模型构造中有效利用频繁序列挖掘算法所获得的局部信息,改进搜索路径,提高算法效率,获得准确结果.     

一种基于偏序排名的高效的多目标演化算法

利用 Better函数对多目标优化问题 (MOP)建立了一种偏序关系 ,并通过这种偏序关系对种群中的个体进行排名 ,设计了一种高效的多目标演化算法 (EMOEA) ,应用有限 Markov链的有关理论证明了此演化算法的收敛性 ,同时对四个 Benchmark函数进行了数值试验 ,测试结果表明 ,新算法在解集分布的均匀性、多样性、精确性以及快速收敛性均优于已有的 MOEA.将此算法推广用于求解经济领域或工程领域的一些难题 ,则在实际中具有广阔的应用前景     

基于形式概念分析的云中虚拟机调度研究

针对云环境中分布式的虚拟机调度问题,首次引入形式概念分析原理,提出基于偏序集的规则算法来发现任务与虚拟机的映射关系。研究工作的重点是首先建立虚拟机任务调度优化模型,并把虚拟机对象转换为形式背景;其次利用偏序关系生成任务与虚拟机的GM偏序图;最后算法先序遍历深度为 n＋1的满二叉树后得出任务与虚拟机的对应关系,并在VC6．0平台中验证了算法的可行性和有效性,为云环境中虚拟机调度提供了一种新的研究途径。     

强偏序时态模式中混合依赖集的成员籍问题

有效的模式分解算法设计中应着重考虑和解决成员籍问题,时态类型间偏序关系在强偏序时态模式中的存在给解决成员籍问题带来了困难。为了有效解决强偏序时态模式中混合依赖集的成员籍问题,提出了给定时态类型上的偏序混合依赖基、强偏序模式混合依赖基、偏序时态函数依赖和偏序时态多值依赖的混合集闭包、强偏序模式混合闭包等概念,给出了求混合依赖集中属性的依赖基、属性集的闭包的算法,并在此基础上给出了强偏序模式混合依赖集成员籍问题的算法,证明了其正确性及可终止性,对该算法的时间复杂度进行了分析。应用实例表明相关理论和算法能解决强偏序混合依赖集中成员籍问题的判定问题,为解决强偏序时态模式规范化问题以及时态数据库设计提供了理论基础。     

一种结合限制的多任务学习策略及其应用

定义任务之间的偏序限制,基于偏序限制可以联系原先独立的任务.分析偏序限制的应用,给出一个协同演化的多任务学习框架,它反复地通过各个任务的独立演化以寻优,通过联合调整以结合偏序限制.给出本框架在构建猪肉预冷损耗曲线过程中的应用:考虑了低湿损耗曲线与中湿损耗曲线间的偏序关系,利用协同演化,在样本量很少时,也能获得合理的低湿和中湿损耗曲线.对于4个标准测试函数的测试显示了本策略对于一般问题的有效性.     

离散格的一种启发式搜索算法

通过定义离散化方案之间的偏序关系以及交、并运算，将各种离散化方案组织成离散格。提出一种搜索离散格的启发式算法，实验表明该算法得到的一致决策表的断点数比已有解更少。     

GM偏序图的构建和基于GM偏序图的规则提取

对形式背景上的G偏序集、M偏序集和GM偏序集的偏序关系作了进一步讨论,提出了对象上邻、对象下邻、属性上邻、属性下邻、对象上界、对象下界、属性上界、属性下界和极大对象下界等概念,并根据上下邻之间的关系给出G偏序图、M偏序图和GM偏序图的构建算法,最后给出了不需要建格而可直接在GM偏序图上进行规则提取的算法,并通过实例验证了算法的有效性。     

命题μ-演算局部模型检测高效算法设计

命题μ-演算局部模型检测算法中,目前最好的算法的时间复杂度与不动点算子交替嵌套深度d呈指数关系。针对命题μ-演算局部模型检测算法的计算过程进行分析,得到迭代计算的中间迭代值间满足的一组偏序关系,然后利用该偏序关系设计了一个局部模型检测算法,算法时间复杂度的指数部分为d/2,大大提高了算法的计算效率。     

基于模糊负反馈算法的可演化安全策略研究

在分析现有访问控制策略研究的基础上,基于模糊负反馈算法,创建一个安全策略可演化的访问控制系统。通过对角色、权限以及安全策略的模糊化处理及分析。给出安全策略的描述方法,定义安全偏序关系。并在此基础上给出安全策略调整的方法,探讨算法调整时机。对用户的访问权限进行判断。在此基础上引入控制论的负反馈原理,对安全策略进行求精、演化,并通过实验初步验证算法的效果。     

基于偏序关系粒范畴的构造方法

目前粒计算理论还没有公认的统一模型,为了解决这个问题,从粒集出发,定义了粒的个体对象间的泛化-例化关系、粒之间的泛包含关系,证明了它们都是偏序关系且具有偏序关系的粒集是一个范畴;定义了粒集的泛交运算,并通过实例给出了基于偏序关系的粒范畴的构造方法,讨论了这种粒范畴的几个性质。这些研究成果说明了基于偏序关系的粒范畴的构造方法是行之有效的,为研究粒范畴的应用问题奠定了基础。     

An introduction to vague complemented ordered sets

The purpose of this paper is to introduce a theory of fuzzily defined complement operations on nonempty sets equipped with fuzzily defined ordering relations. Many-valued equivalence relation-based fuzzy ordering relations (also called vague ordering relations) provide a powerful and a comprehensive mathematical modelling of fuzzily defined partial ordering relations. For this reason, starting with a nonempty set X equipped with a many-valued equivalence relation and a vague ordering relation, a fuzzily defined complement operation (called a vague complement operation) on X will be formulated by means of the underling many-valued equivalence relation and vague ordering relation. Because of the fact that the practical implementations of vague complement operations basically depend on their representation properties, a considerable part of this paper is devoted to the representations of vague complement operations. In addition to this, the present paper provides various nontrivial examples for vague complements, and introduces a many-valued logical interpretation of quantum logic as a real application of vague complements.     

Existence of χ‐efficient solution of multiobjective fractional programming problem with bounded parameters

In this paper, a methodology is developed to solve a multiobjective fractional programming problem in which the coefficients of the objective functions and constraints are intervals. This model is transformed into an interval‐free equivalent optimization problem. A new partial ordering is introduced and the relation between the original problem and the transformed problem is established using this partial ordering. The proposed methodology is illustrated through a numerical example.     

区间序信息系统及其属性约简算法

在不含决策属性的区间序信息系统中,区间偏序关系的不完备性造成信息流失。针对该问题,提出一种新的基于区间模糊数的区间序全序关系,以此建立区间序信息系统,并分析其相关上、下近似的单调性和包含性。采用不可区分函数的方法,给出区间序信息系统的属性约简算法,并通过算例验证了该算法的有效性。     

Computing full disjunction using COJO

The Internet has provided users with access to wealth of information available on the Web, a considerable amount of which is semi-structured. In recent times, there has grown a need to access this information in an interpretable and meaningful way. One way to access this information is by transforming it into relations and integrating the relations to arrive at a universal relation thus ensuring simple and powerful searching of the underlying semi-structured data. Several operations exist for integrating these relations, like outer union, natural inner join, natural outer join etc., of which natural outer join has been found to be most effective in terms of achieving meaningful results i.e. full disjunction of the relations. Since natural outer join is non-associative, for more than two relations only some of the natural outer join ordering may lead to full disjunction. The Correct Outer Join Ordering (COJO) strategy proposed in this paper computes such natural outer join ordering of relations leading to full disjunction. It is further shown that the natural outer join ordering of relations produced by algorithm COJO compares well with the well-known algorithm SOJO on performance parameters. This paper is an expanded version of [24].     

Partial ordering of information granulations: a further investigation

The notion of information systems provides a convenient tool for knowledge representation of objects in terms of their attribute values, while partial ordering is usually used to research the rough monotonicity of an uncertainty measure in information systems. In this paper, we first reveal the limitations of existing partial orderings to describe information granulations in information systems with several illustrative examples. Then, a generalized partial ordering with a set‐size nature is proposed to overcome their shortcoming and some of its important properties are derived. Finally, we prove that several existing information granulations all satisfy the granulation monotonicity induced by the proposed partial ordering. The presented partial ordering appears to be well suited to characterize the nature of information granulations in an information system. These results will be very helpful for studying granular computing and uncertainty in information systems.     

Optimal interval enclosing of certain sets of matrices,with application to monotone enclosing of square roots

In this paper, two kinds of partial ordering for symmetric matrices are related to each other, namely, the natural partial ordering ≤ generated by the coneK of elementwise nonnegative matrices, and the definite partial ordering \( \leqslant \cdot\) generated by the coneK _D of nonnegative definite matrices. The main result of this paper shows how a matrix interval in the sense of the definite partial ordering can be enclosed between optimal bounds with respect to the natural partial ordering. By means of this result, it is possible to compute a numerically practicable inclusion based on the natural partial ordering from a given inclusion of some matrix with the definite partial ordering. In this way, an always and moreover quadratically convergent method of elementwise enclosing the square root of a positive definite, symmetric matrix can be constructed.     

Pruning with improving sequences in lazy functional programs

This paper presents a library based on improving sequences and demonstrates that they are effective for pruning unnecessary computations while retaining program clarity. An improving sequence is a monotonic sequence of approximation values of a final value that are improved gradually according to some ordering relation. A computation using improving sequences proceeds by demanding for the next approximation value. If an approximation value in the middle of the improving sequence has sufficient information to yield the result of some part of the program, the computations that produce the remaining values can be pruned. By combining suitable improving sequences and primitive functions defined for the sequences, we can write efficient programs in the same form as simple and naive programs. We give examples that show the effectiveness of improving sequences and show by program calculation that a simple minimax-like program using improving sequences implements a well-known branch-and-bound searching algorithm.