TLWCC：一种双层子空间加权协同聚类算法

协同聚类是对数据矩阵的行和列两个方向同时进行聚类的一类算法。本文将双层加权的思想引入协同聚类,提出了一种双层子空间加权协同聚类算法(TLWCC)。TLWCC对聚类块(co-cluster)加一层权重,对行和列再加一层权重,并且算法在迭代过程中自动计算块、行和列这三组权重。TLWCC考虑不同的块、行和列与相应块、行和列中心的距离,距离越大,认为其噪声越强,就给予小权重;反之噪声越弱,给予大权重。通过给噪声信息小权重,TLWCC能有效地降低噪声信息带来的干扰,提高聚类效果。本文通过四组实验展示TLWCC算法识别噪声信息的能力、参数选取对算法聚类结果的影响程度,算法的聚类性能和时间性能。     

MC-MLAS: Multi-channel Minimum Latency Aggregation Scheduling in Wireless Sensor Networks

Data aggregation is a key, yet time-consuming functionality in wireless sensor networks (WSNs). Multi-channel design is a promising technique to alleviate interference as a primary reason for long latency of TDMA aggregation scheduling. Indeed, it provides more potential of parallel transmissions over different frequency channels, thus minimizing time latency. In this paper, we focus on designing a multi-channel minimum latency aggregation scheduling protocol, named MC-MLAS, using a new joint approach for tree construction, channel assignment, and transmission scheduling. To our best knowledge, this is the first work in the literature which combines orthogonal channels and partially overlapping channels to consider the total latency involved in data aggregation. Extensive simulations verify the superiority of MC-MLAS in WSNs.     

基于模糊决策的风力发电产业评价研究

根据风力发电技术产业的特点,构建改进层次分析与模糊一致矩阵相结合的方案决策数学模型,该模型既可以减少确定判断矩阵的盲目性,又可以避开评价体系中各等级间的隶属度确定问题,使评价结果更加可靠,适合于信息尚不完整、受主观因素影响较强的评价。实例验证了这一模型的合理性、可行性和有效性,具有实用价值。     

用聚类预报模型预报三峡水库来水量的探讨

为了开展三峡水库入库来水量长期预报,从北半球500 hPa高度场、太平洋海温场、北半球100 hPa高度场、北半球地面气压场与74项环流特征指数作为预报因子,采用回归方程求解和回归效果检验,建立回归聚类预报物理模型,对三峡水库6～8月各月平均来水量进行了长期预报分析。结果表明,三峡水库6~8月份各月来水量回归聚类预报的技术路线是可行的,正、负距平符号一致的概率能达到80%以上,效果较好,基本上可以满足生产需要。回归聚类预报物理模型具有一定的应用推广价值。     

A general method of spatio-temporal clustering analysis

Spatio-temporal clustering has been a hot topic in the feld of spatio-temporal data mining and knowledge discovery.It can be employed to uncover and interpret developmental trends of geographic phenomenon in the real world.However,existing spatio-temporal clustering methods seldom consider both spatiotemporal autocorrelations and heterogeneities among spatio-temporal entities,and the coupling in space and time has not been well highlighted.In this paper,a unifed framework for the clustering analysis of spatio-temporal data is proposed,and a novel spatio-temporal clustering algorithm is developed by means of a spatio-temporal statistics methodology and intelligence computation technology.Our method is applied successfully to fnding spatio-temporal cluster in China’s annual temperature database for the period 1951 1992.     

Ranking Approach for the User Story Prioritization Methods

The AHP （analytic hierarchy process） has been applied in many fields and especially to complex engineering problems and applications. AHP is capable of structuring decision problems and finding mathematically determined judgments built on knowledge and experience. This suggests that AHP should prove useful in agile software development, where complex decisions occur routinely. This paper describes a ranking approach to help stakeholders select the best prioritization method for prioritizing the user stories.     

天津市于桥水库饮用水源地保护对策研究

于桥水库作为天津市最重要的饮用水水源地,其库区水体氮、磷浓度接近国家标准阈值,亟需采取保护防治措施缓解水体氮、磷污染负荷压力。本文基于水库型饮用水水源地环境保护技术框架的一般思路,开展了对于桥水库水环境治理技术方案的分析研究。首先,使用GWLF(普适流域负荷函数)模型对水库周边流域污染源负荷进行识别与负荷解析;之后,基于最佳管理实践(BMP)和低影响开发(LID)的理念和方法,同时根据于桥水库的具体实际情况,提出相应的工程治理措施,并采用BATHTUB模型对各工程措施进行环境效益评估计算;最后使用模糊层次分析法(FAHP)对各工程措施进行择优分析,得出最佳治理实施方案。     

一种新的低压电力线载波网络软件路由器设计

针对窄带电力线网络节点通信状态变化剧烈和通信成功率低的问题,提出了一种新的基于节点相关度的动态网络分簇软件路由器的设计方法。该路由器根据接收信号强度、历史抄通概率和网络连通度选取簇头节点,根据节点相关度确定簇内成员;当部分网络节点以现有路径不能正常通信时采取基于邻居节点数目的概率泛洪机制重构网络,可保证数据的即时传输。分析表明这种路由器具有灵活性、实用性和有效性。     

基于时态层次链的Data Cube 多版本维护方案

针对Data Cube的模式变动造成的多版本问题,对时态聚集关系与时态层次链进行了形式化描述,并基于这些关系实现了多个版本的Data Cube的统一生成算法,不仅可以高效地进行Data Cube多个版本的维护,而且在OLAP查询也可以基于时态层次链来执行,从而提高系统的整体效率。