Interactive fuzzy stochastic multi-level 0–1 programming using tabu search and probability maximization

In this paper, we consider interactive fuzzy programming for multi-level 0–1 programming problems involving random variable coefficients both in objective functions and constraints. Following the probability maximization model together with the concept of chance constraints, the formulated stochastic multi-level 0–1 programming problems are transformed into deterministic ones. Taking into account vagueness of judgments of the decision makers, we present interactive fuzzy programming. In the proposed interactive method, after determining the fuzzy goals of the decision makers at all levels, a satisfactory solution is derived efficiently by updating satisfactory levels of the decision makers with considerations of overall satisfactory balance among all levels. For solving the transformed deterministic problems efficiently, we also introduce novel tabu search for general 0–1 programming problems. A numerical example for a three-level 0–1 programming problem is provided to illustrate the proposed method.     

Determination of temporal information granules to improve forecasting in fuzzy time series

Partitioning the universe of discourse and determining intervals containing useful temporal information and coming with better interpretability are critical for forecasting in fuzzy time series. In the existing literature, researchers seldom consider the effect of time variable when they partition the universe of discourse. As a result, and there is a lack of interpretability of the resulting temporal intervals. In this paper, we take the temporal information into account to partition the universe of discourse into intervals with unequal length. As a result, the performance improves forecasting quality. First, time variable is involved in partitioning the universe through Gath–Geva clustering-based time series segmentation and obtain the prototypes of data, then determine suitable intervals according to the prototypes by means of information granules. An effective method of partitioning and determining intervals is proposed. We show that these intervals carry well-defined semantics. To verify the effectiveness of the approach, we apply the proposed method to forecast enrollment of students of Alabama University and the Taiwan Stock Exchange Capitalization Weighted Stock Index. The experimental results show that the partitioning with temporal information can greatly improve accuracy of forecasting. Furthermore, the proposed method is not sensitive to its parameters.     

Incrementally building frequent closed itemset lattice

A concept lattice is an ordered structure between concepts. It is particularly effective in mining association rules. However, a concept lattice is not efficient for large databases because the lattice size increases with the number of transactions. Finding an efficient strategy for dynamically updating the lattice is an important issue for real-world applications, where new transactions are constantly inserted into databases. To build an efficient storage structure for mining association rules, this study proposes a method for building the initial frequent closed itemset lattice from the original database. The lattice is updated when new transactions are inserted. The number of database rescans over the entire database is reduced in the maintenance process. The proposed algorithm is compared with building a lattice in batch mode to demonstrate the effectiveness of the proposed algorithm.     

二乙烯基苯改性煤沥青的流变行为

研究了二乙烯基苯(DVB)改性煤沥青的流变行为.采用SEM和EDAX对改性前后沥青的形貌和组成进行分析,采用旋转黏度计测试改性沥青的流变性能.研究表明:改性沥青中出现分布均匀的微纤;随着改性沥青中甲苯可溶物含量的减少,其黏性流动活化能变大;改性沥青的剪切速率越高,改性沥青的表现黏度越小.     

双渠道供应链中服务对定价和需求的影响研究

研究了集中式决策和基于Stackelberg博弈这两种情况下的双渠道供应链的定价、服务及需求的关系。制造商和零售商提供的服务对价格、需求会产生影响,渠道商改善服务有利于本渠道价格的提高,同时会影响到另一渠道的定价,影响程度与双渠道决策模式相关。与服务对定价的影响不同,渠道商提供的服务对本渠道需求产生的影响是双向的,当服务水平在一定的范围内,改善服务可以增加本渠道市场需求,降低另一渠道需求;当服务水平过高,继续改善服务不仅不能增加需求反而减少需求,同时对另一渠道的需求产生影响,这种影响与消费者市场类型存在密切关系。当消费者市场属于价格敏感型时,服务水平存在一个帕累托区间,任一渠道商改善服务都会促进双渠道需求的增加。     

多频带谱减法用于生态环境声音分类

基于人类听觉特性的Mel频率倒谱系数广泛用于声音识别,然而在生态环境中噪声的出现导致其识别率剧减。提出一种在噪声背景下生态环境声音分类方法。利用非线性多频带谱减法对声音功率谱进行去噪处理并提取改进Mel频率倒谱系数,有效削弱不同频率段噪声功率谱干扰。利用支持向量机良好的鲁棒性和抗噪能力对含有噪声的生态环境声音进行分类。实验表明该方法能有效在噪声背景下对生态环境声音准确分类。     

基于运行时模型的多样化云资源管理方法

多样化的受管资源和不断变化的管理需求,使得云管理面临很大的难度和复杂度.面对一个新的特定的管理需求,管理员往往是在已有管理软件的基础上进行二次开发,通过管理功能的获取和组织来构造新的管理系统.然而,由于缺乏通用的方法,二次开发的难度和复杂度依然很大.为了能够根据管理需求快速定制、集成、扩展已有的管理软件,提出一种基于运行时模型的多样化云资源管理方法.首先,在系统管理接口的基础上构造不同受管资源的运行时模型;其次,通过对不同的运行时模型进行合并,来构造包含所有目标受管资源的组合模型;最后,通过组合模型到用户特定模型的转换,来满足特定的管理需求.在OpenStack与Hyperic两款独立管理软件的基础上,实现了基于运行时模型的虚拟机软、硬件资源统一管理系统,验证了方法的可行性和有效性.     

应用传感器的Android游戏开发

介绍手机常用的传感器类型。讲解列举手机中传感器安装的方法,阐述手机传感器的参数及使用方法。以加速度传感器为例,讨论了手机传感器在游戏开发中的应用,详细分析了代码。对初学者有很大帮助。     

基于模糊期望值的模糊DEA 交叉效率评价方法

基于模糊DEA的交叉效率评价方法研究是一个崭新的研究课题,有着广阔的应用前景。结合基于模糊期望值的模糊 DEA 模型和交叉效率原理,提出一种新的交叉效率的评价方法。该方法首先求出基于模糊期望值的最优效率值权重,然后由这组模糊最优权重求解他评效率并构造交叉效率矩阵,最后根据求出的模糊期望交叉效率值对各DMU进行排序。