Case‐based approach for supporting strategy decision making

The practice of strategy decision making proves that when the management board is strongly limited in its capacity to take rational actions, specifically in the context of great decision complexity and uncertainty, it is considered good practice to refer to experience through reasoning by analogy. In this paper, we would like to concentrate on supporting strategic decisions in small and medium enterprises (SMEs). The complexity of analogy‐based reasoning has its roots in an attempt to solve new problems based on past cases from a different domain, while we will focus on case‐based approach for a single domain. Additionally, we have chosen case‐based reasoning as a suitable decision‐making paradigm because it is corresponds to managers’ decision‐making behaviour. We present the STRATEGOS case‐based reasoning system for supporting strategic decision making by SMEs management boards and then the system evaluation by the dozens of chief executive officers (CEOs) from SMEs is presented. The results of the survey are promising and show the remarkable correspondence of the proposed solution with expectations and strategic behaviour of CEOs.     

An integrated DEMATEL and Fuzzy ANP techniques for evaluation and selection of outsourcing provider for a telecommunication company

In recent years, strategy aspects related to core competency, risk analysis and organizational flexibility especially have been growing. This trend has led researchers and industries to become more interested in the multi-criteria decision making (MCDM) models for selecting outsourcing providers. The efficiency of decision-making mostly depends on the ability of decision-makers analyzing the complex cause and effect relationship between criteria and taking effective actions based on the analysis. Using an analytical method to select the most eligible outsourcing provider is significant for a company which desires to improve its competitiveness. In this study, a fuzzy integrated multi-criteria decision making method for evaluation and determination of an outsourcing provider for a telecommunication company is analyzed by using DEMATEL and Fuzzy ANP multi-criteria decision making techniques. First, DEMATEL method is used in order to put forward the interrelationship among the main criteria which are determined in the study for outsourcing selection process. Then, local weights of the sub-criteria and sub-subcriteria are calculated by Fuzzy ANP approach on the basis of cause-effect relationships that are exposed through DEMATEL method. The local weights are put into ANP supermatrix, and calculations are implemented to select out the most eligible outsourcing provider.     

一种基于多属性决策的DDoS防护措施遴选方法

DDoS攻击是网络中最大的威胁之一,选取合适的防护措施,能够更加有效地保护目标网络和目标系统.现有的评价方法对于防护措施选择的指导性不足.针对该问题,首先构建了面向DDoS攻击的防护措施遴选模型(DCSM).在此基础之上,提出基于多属性决策的DDoS防护措施遴选算法.以多属性决策方法综合考虑各方面评估指标;从攻防两方面,以基于历史攻击偏好的方法和熵权法计算重要性权重,消除了传统评价方法中人为指定权重带来的主观性影响.提出的方法为防护措施的选择提供了参考,并通过模拟实验验证了方法的适用性和有效性.     

基于网络图的产品生产、运输、定价综合决策模型

针对大型垄断厂商在商品生产、运输、定价决策中独立考虑生产定价和运输两个环节的弊端, 提出一种将产量决策、运输决策和定价决策3 个环节作为一个系统进行考虑的综合决策模型. 借助利润网络图, 构建同时考虑生产及运输成本以及市场需求的商品生产、运输和定价综合决策模型, 并探讨模型的解法及其理论基础. 通过给出的应用案例表明, 相比传统决策模型, 利用综合决策模型可以提高15.50% 的利润.

     

不一致决策表规则获取的粒计算方法

针对不一致决策表的规则获取,从属性多粒度角度考虑,按粒度由粗到细将决策表划分成不同的粒度空间,通过定义相容粒关系矩阵和不相容粒关系矩阵,并充分挖掘隐含在矩阵中的启发式信息,实现对不同粒度空间确定性规则和不确定性规则的获取.最后,从实例分析以及UCI测试对算法进行验证,并与现有算法进行实验对比,实验结果与分析表明了所提出算法的可行性和有效性,而且按此方法获取的规则集的泛化能力更强.     

基于云计算的多路网络流媒体分布式最优存储与分配策略

针对云计算系统在执行任务过程中的能量消耗过多、处理速度不理想等情况,提出一种基于云计算的多路网络流媒体分布式最优存储与分配策略.通过构建基于云计算的数学模型来分析执行任务时的能量消耗情况,采用基于虚拟调度机制的分布式最优存储策略来实现在满足存储需求的情况下减少服务器进行存储时的能量消耗总量,最小化存储成本,并采用基于动态决策规则的分配策略来根据服务器的功率、性能以及负载情况进行任务调度,使云计算系统在满足服务质量要求的条件下,充分利用系统运作能耗,不产生过多空闲能耗.实验及结果分析表明,所提出的分布式最优存储与分配策略在节省能量消耗、提升运行速度上发挥了较好的效果.     

Fuzzy decision fusion of complementary experts based on evolutionary cepstral coefficients for phoneme recognition

Optimal representation of acoustic features is an ongoing challenge in automatic speech recognition research. As an initial step toward this purpose, optimization of filterbanks for the cepstral coefficient using evolutionary optimization methods is proposed in some approaches. However, the large number of optimization parameters required by a filterbank makes it difficult to guarantee that an individual optimized filterbank can provide the best representation for phoneme classification. Moreover, in many cases, a number of potential solutions are obtained. Each solution presents discrimination between specific groups of phonemes. In other words, each filterbank has its own particular advantage. Therefore, the aggregation of the discriminative information provided by filterbanks is demanding challenging task. In this study, the optimization of a number of complementary filterbanks is considered to provide a different representation of speech signals for phoneme classification using the hidden Markov model (HMM). Fuzzy information fusion is used to aggregate the decisions provided by HMMs. Fuzzy theory can effectively handle the uncertainties of classifiers trained with different representations of speech data. In this study, the output of the HMM classifiers of each expert is fused using a fuzzy decision fusion scheme. The decision fusion employed a global and local confidence measurement to formulate the reliability of each classifier based on both the global and local context when making overall decisions. Experiments were conducted based on clean and noisy phonetic samples. The proposed method outperformed conventional Mel frequency cepstral coefficients under both conditions in terms of overall phoneme classification accuracy. The fuzzy fusion scheme was shown to be capable of the aggregation of complementary information provided by each filterbank.     

Group decision making based on incomplete multiplicative and fuzzy preference relations

The main aim of this paper is to investigate the group decision making on incomplete multiplicative and fuzzy preference relations without the requirement of satisfying reciprocity property. This paper introduces a new characterization of the multiplicative consistency condition, based on which a method to estimate unknown preference values in an incomplete multiplicative preference relation is proposed. Apart from the multiplicative consistency property among three known preference values, the method proposed also takes the multiplicative consistency property among more than three values into account. In addition, two models for group decision making with incomplete multiplicative preference relations and incomplete fuzzy preference relations are presented, respectively. Some properties of the collective preference relation are further discussed. Numerical examples are provided to make a discussion and comparison with other similar methods.     

概率模型检测技术在机器人路径规划中的应用

在机器人路径规划的实际应用中,针对机器人移动行为可能会受到外界环境影响的难题,提出了一种采用概率模型检测技术进行路径规划的新方法。首先,分析环境中的主要影响因素,将机器人的移动行为看作一个不确定事件,构建马尔可夫决策过程(MDP)模型。然后,采用概率计算树逻辑(PCTL)公式描述模型属性,表达机器人复杂多样的目标任务。最后,运用PRISM平台对模型进行分析和验证,得到满足属性的全局优化路径和定量数据。仿真结果表明,上述方法不仅能够保障机器人在障碍物环境中无碰撞移动,而且可以避开环境相对复杂的区域,保证机器人以最大概率完成任务。对比试验证明上述方法的正确性和有效性。     

基于相关系数的决策树优化算法

通过分析ID3算法的基本原理及其多值偏向问题,提出了一种基于相关系数的决策树优化算法。首先通过引进相关系数对ID3算法进行改进,从而克服其多值偏向问题,然后运用数学中泰勒公式和麦克劳林公式的性质,对信息增益公式进行近似简化。通过具体数据的实例验证,说明优化后的ID3算法能够解决多值偏向问题。标准数据集UCI上的实验结果表明,在构建决策树的过程中,既提高了平均分类准确率,又降低了构建决策树的复杂度,从而还缩短了决策树的生成时间,当数据集中的样本数较大时,优化后的ID3算法的效率得到了明显的提高。