基于模糊聚类和粗糙集提取我国经济增长的模糊规则

提出了一种基于模糊软分类和粗糙集理论来提取模糊规则的一种算法.该算法分为3个步骤①通过模糊软分类对样本进行模糊划分,得到隶属度矩阵;②运用粗糙集理论和得到的隶属度矩阵生成初始决策表;③简化决策表,提取规则.最后运用该算法提取我国经济增长的模糊规则.     

有模糊时间窗的车辆调度组合干扰管理研究

研究带有模糊时间窗的车辆调度组合干扰管理模型及其混合遗传算法.采用时间窗模糊化处理方法,定义客户满意度函数,根据干扰管理思想对车辆调度中组合性干扰事件进行分析,从配送路径、配送成本和客户满意度三个方面进行干扰辨识与度量,建立基于模糊时间窗的车辆调度组合干扰管理模型;构造模型求解的混合遗传算法,将最佳客户插入规则与遗传算法结合,同时在算法中嵌入模糊优化程序以处理问题的模糊特征;进行数值实验,实验结果验证了模型与算法的有效性.     

基于模糊综合评价的煤矿本质安全数据挖掘

本文应用模糊综合评价法得到煤矿本质安全等级和指标体系,应用模糊聚类算法确定主关键条件属性集,使用模糊数据挖掘出评估对象中煤矿本质安全等级同评估指标之间的规则知识,以一个实例为对象建立的煤矿本质安全模糊数据挖掘验证了该方法的可行性。     

一种基于信息熵与K均值迭代模型的模糊聚类算法

本文提出了基于信息熵和K均值算法混合迭代模糊聚类的细分模型,解决了模糊聚类的原型初始化参数问题。将信息熵和K均值算法引入模糊聚类中进行分析,并结合测试样本数据进行实际分析,与传统方法相比,取得了较好的效果。     

模糊规则插值法在约简模糊系统中的应用

本文讨论模糊规则插值法及其在简化模糊决策系统中的应用.在稀疏模糊规则库中,可以利用模糊规则插值法实现模糊推理.而利用模糊插值法进行模糊规则库的约简,则是在规则库中发现一些规则,它们能由其它规则通过插值机制近似表示,这些规则是冗余的规则,可以从规则中去除.     

智能决策支持系统中定量特征规则的挖掘方法研究

定量特征规则通过将定量信息与规则相结合定量地反映了概念的主要特征和次要特征,面向属性的归纳学习算法是在数据库中挖掘定量特征规则的一个重要手段,但直接采用这种方法往往会使同一个概念有不同的特征描述,这种现象必然降低规则对决策的参考价值.本文提出了一个测量定量特征规律有效性的计算指标,并结合该指标设计出一个新的面向属性的归纳算法,该算法使定量特征规则在有效性上达到最优,避免了同一概念有不同的特征规则的现象.     

基于领域知识和聚类的关联规则深层知识发现研究

本文针对传统关联规则挖掘算法产生大量冗余规则,提出了对关联规则结果进行二次挖掘,并设计了算法对挖掘出的关联规则进行聚类,然后基于已有领域知识对聚类后的关联规则进行新颖度评价,对于新颖度较高价值较大的关联规则可以存储于领域知识库用于决策使用或再次挖掘过程。该算法有效的减少的规则的数量,提高了规则的新颖性和精确度,对商业应用具有很高的价值。文章最后使用UCI开源数据进行了实验分析,并验证了该算法的有效性。     

灾后模糊需求情境下考虑救援公平性的应急物资调度问题模型与算法研究

在重大灾害发生初期,由于受灾地区对应急物资的需求激增,合理的应急物资分配有助于提高救援效率。本文考虑受灾点应急物资需求具有模糊属性,将需求物资用三角模糊数表示,以受灾群众损失最小、体现救援公平性的受灾点应急物资满意度方差最小及应急救援成本最小为目标,构建了灾后初期应急物资调度的多目标模糊优化模型,并采用改进的粒子群算法对模型进行求解。该算法在粒子群算法的基础上采取天牛寻找食物的策略,将单一粒子分为左、中、右三个粒子,并结合单纯形算子和模拟退火策略,使算法不易陷入局部收敛。本文通过算例进行模拟实验表明,所提出的模型和算法可以有效解决重大灾害事件下应急物资的合理分配问题,且改进算法的性能更优。     

奇异值分解在重构模糊决策系统规则库中的应用

利用SVD技术重构PSG模糊规则库,降低规则的数量。根据矩阵奇异值的性质,适当取舍模糊规则库后件矩阵Ω的奇异值,得到Ω的近似表示Ω,利用Ω重新构建规则库,新规则库的输入变量域的维数比原规则库的维数小,从而有效地降低了模糊规则数。仿真结果证明了该方法是有效的。     

一种基于PIM与核方法的模糊聚类新算法

本文针对模糊C均值聚类在大数据量时收敛较慢以及不能对多种数据结构有效聚类的缺点,结合PIM算法与核方法提出了一种新的高效聚类算法———KPIM算法,并从理论上证明了该算法的收敛性.最后利用标准实验数据IRIS数据集测试,结果表明KPIM算法在保证收敛速度的同时,聚类效果更有效.     

Visualizing association rules in hierarchical groups

Association rule mining is one of the most popular data mining methods. However, mining association rules often results in a very large number of found rules, leaving the analyst with the task to go through all the rules and discover interesting ones. Sifting manually through large sets of rules is time consuming and strenuous. Although visualization has a long history of making large amounts of data better accessible using techniques like selecting and zooming, most association rule visualization techniques are still falling short when it comes to large numbers of rules. In this paper we introduce a new interactive visualization method, the grouped matrix representation, which allows to intuitively explore and interpret highly complex scenarios. We demonstrate how the method can be used to analyze large sets of association rules using the R software for statistical computing, and provide examples from the implementation in the R-package arulesViz.     

Improvements to MCS algorithm for the maximum clique problem

In this paper we present improvements to one of the most recent and fastest branch-and-bound algorithm for the maximum clique problem—MCS algorithm by Tomita et al. (Proceedings of the 4th international conference on Algorithms and Computation, WALCOM’10, pp. 191–203, 2010). The suggested improvements include: incorporating of an efficient heuristic returning a high-quality initial solution, fast detection of clique vertices in a set of candidates, better initial colouring, and avoiding dynamic memory allocation. Our computational study shows some impressive results, mainly we have solved p_hat1000-3 benchmark instance which is intractable for MCS algorithm and got speedups of 7, 3000, and 13000 times for gen400_p0.9_55, gen400_p0.9_65, and gen400_p0.9_75 instances correspondingly.     

Improved approximation algorithms for the max-bisection and the disjoint 2-catalog segmentation problems

We consider the max-bisection problem and the disjoint 2-catalog segmentation problem, two well-known NP-hard combinatorial optimization problems. For the first problem, we apply the semidefinite programming (SDP) relaxation and the RPR² technique of Feige and Langberg (J. Algorithms 60:1–23, 2006) to obtain a performance curve as a function of the ratio of the optimal SDP value over the total weight through finer analysis under the assumption of convexity of the RPR² function. This ratio is shown to be in the range of [0.5,1]. The performance curve implies better approximation performance when this ratio is away from 0.92, corresponding to the lowest point on this curve with the currently best approximation ratio of 0.7031 due to Feige and Langberg (J. Algorithms 60:1–23, 2006). For the second problem, similar technique results in an approximation ratio of 0.7469, improving the previously best known result 0.7317 due to Wu et al. (J. Ind. Manag. Optim. 8:117–126, 2012).     

‘Strong Personalities’ and ‘Strong Institutions’ Mediated by a ‘Strong Third Force’: Thinking ‘Systems’ in Corruption Control

Corruption in public sector is a complex, ‘messy’ and ‘fuzzy’ phenomenon which involves calculus machinations between actors and constantly growing in sophistication. Consequently, an attempt to prevent, control or fight it requires systems thinking that ranges from public officials with integrity and personal ethics [strong personalities]; administrative rules and procedures as well as governments adopting, enforcing and monitoring appropriate systems [strong institutions]. This paper provides a systems approach to enhancing public sector ethics through ‘a corruption control tripod’ in preventing, controlling and combating corruption in all its forms. This framework discusses three overarching pillars and argues that adopting a reductionist approach in corruption control would yield futility; there is a need for synthesis so that each one would reinforce the other.     

A refined algorithm for maximum independent set in degree-4 graphs

The maximum independent set problem is one of the most important problems in theoretical analysis on time and space complexities of exact algorithms. Theoretical improvement on upper bounds on time complexity to solve this problem in low-degree graphs can lead to an improvement on that to the problem in general graphs. In this paper, we derive an upper bound \(O^*(1.1376^n)\) on the time complexity of a polynomial-space algorithm that solves the maximum independent set problem in an n-vertex graph with degree bounded by 4, improving all previous upper bounds on the time complexity of exact algorithms to this problem. Our algorithm is a branch-and-reduce algorithm and analyzed by using the measure-and-conquer method. To make an amortized analysis of the running time bound, we use an idea of “shift” to save some decrease of the measure from good branches to bad branches. Our algorithm first deals with small vertex cuts and vertices of degree \({\ge }5\), which may be created in our algorithm even if the input graph has maximum degree 4, then eliminates cycles of length 3 and 4 containing degree-4 vertices, and finally branches on degree-4 vertices. We invoke an exact algorithm for this problem in graphs with maximum degree 3 directly when the graph has no vertices of degree \({\ge }4\). Branching on degree-4 vertices on special local structures will be the bottleneck case, and we carefully design rules of choosing degree-4 vertices to branch on so that the resulting instances after branching decrease the measure effectively in the next step.     

Insider ownership and corporate performance: evidence from Germany

In this paper we address the question whether insider ownership affects corporate performance. Evidence from studies dealing with Anglo-Saxon countries is rather inconclusive, especially because results seem to be significantly affected by endogeneity. Economically, this is due to the fact that in these countries insider ownership seems to be mainly driven by management’s compensation contracts. We argue that Germany is different in this regard, as insider ownership is often related to family control, stock-based compensation is less widespread, and the market for corporate control used to be less developed. Starting from this presumption, our data allows an unbiased observation as to whether insider ownership affects firm performance. Using a pooled data set of 648 firm observations for the years 2003 and 1998, we find evidence for a positive and significant relationship between corporate performance—as measured by stock price performance, market-to-book ratio and return on assets—and insider ownership. This relationship seems to be rather robust, even if we account for potential endogeneity by applying a 2SLS regression approach. Furthermore, the results hold for a sub-sample of firms that did not have a stock-based compensation program in place. Moreover, we find outside block ownership as well as more concentrated insider ownership to have a positive impact on corporate performance. Overall, the results indicate that ownership structure might be an important variable explaining the long term value creation in the corporate sector.

Power domination with bounded time constraints

Based on the power observation rules, the problem of monitoring a power utility network can be transformed into the graph-theoretic power domination problem, which is an extension of the well-known domination problem. A set \(S\) is a power dominating set (PDS) of a graph \(G=(V,E)\) if every vertex \(v\) in \(V\) can be observed under the following two observation rules: (1) \(v\) is dominated by \(S\), i.e., \(v \in S\) or \(v\) has a neighbor in \(S\); and (2) one of \(v\)’s neighbors, say \(u\), and all of \(u\)’s neighbors, except \(v\), can be observed. The power domination problem involves finding a PDS with the minimum cardinality in a graph. Similar to message passing protocols, a PDS can be considered as a dominating set with propagation that applies the second rule iteratively. This study investigates a generalized power domination problem, which limits the number of propagation iterations to a given positive integer; that is, the second rule is applied synchronously with a bounded time constraint. To solve the problem in block graphs, we propose a linear time algorithm that uses a labeling approach. In addition, based on the concept of time constraints, we provide the first nontrivial lower bound for the power domination problem.     

The organization of project evaluation under competition

This article examines the optimal organizational form of project evaluation under competition. The evaluations are carried out by two fallible screening units that sequentially assess projects. Screening can be organized as a hierarchy or a polyarchy. We show that as competitive pressure rises, the polyarchy becomes less attractive. Therefore, different organizational forms might be found in different industries depending on the degree of competition. In addition, we examine endogenous screening rules under competition: For symmetric situations, we show that polyarchies will employ higher decision thresholds compared to hierarchies. Nonetheless, as in the case of exogenous screening rules, the hierarchy becomes more attractive the higher the degree of competition.

Generating a smallest binary tree by proper selection of the longest edges to bisect in a unit simplex refinement

In several areas like global optimization using branch-and-bound methods for mixture design, the unit n-simplex is refined by longest edge bisection (LEB). This process provides a binary search tree. For \(n>2\), simplices appearing during the refinement process can have more than one longest edge (LE). The size of the resulting binary tree depends on the specific sequence of bisected longest edges. The questions are how to calculate the size of one of the smallest binary trees generated by LEB and how to find the corresponding sequence of LEs to bisect, which can be represented by a set of LE indices. Algorithms answering these questions are presented here. We focus on sets of LE indices that are repeated at a level of the binary tree. A set of LEs was presented in Aparicio et al. (Informatica 26(1):17–32, 2015), for \(n=3\). An additional question is whether this set is the best one under the so-called \(m_k\)-valid condition.