基于模糊神经网络的房地产价格评估问题研究

提出了一种基于神经模糊推理系统的商品住宅价格评估模型,分析了影响商品住宅价格的因素,给出了商品住宅价格评估指标体系,探讨了模型建立的原理及算法步骤.计算实例说明了该模型用于商品住宅价格准确评估的有效性和可行性,为房地产价格评估提供了科学的方法.     

对造纸行业ERP系统建设重点的讨论

实施以ERP系统为核心的管理创新已成为企业的发展趋势，文章对在造纸企业实施ERP需要注意的问题进行了综述，指出了现存的困难并对其改进方法进行了讨论。     

基于RBF网络的二手房价格评估

为了反映评估过程的非线性,合理确定二手房价格,通过分析传统评估方法的不足,提出了基于径向基函数(RBF)神经网络的二手房价格评估模型.模型包括数据库、输入、筛选、学习、测试、评估、输出、知识库8个模块.利用该模型对杭州市二手房市场进行了实证分析,网络测试取得了良好的结果,证明了基于RBF网络的二手房价格评估方法的实用性和有效性.     

基于企业竞争力的供应链管理评价指标体系

论述了供应链管理与企业竞争力的内在关系，阐明了在企业竞争力评价中从供应链管理角度反映企业竞争力的必要性和相应的原则．在构建评价指标体系框架的基础上，对各评价指标涵义、计算式及其在评价中的意义作了较为详尽的分析和描述．并结合某企业进行了实际评价和分析．     

延吉市饮用水源水质评价和保护对策的探讨(Ⅱ)

通过水源地库水、入库地表水、背景源头水的监测和属地污染源调查，制定和探讨水源保护的对策和防治措施．     

基于GIS的水利信息系统设计与实现

详细介绍了基于GIS的水利信息系统设计与实现。首先介绍了开发系统的需求分析，以及系统的体系结构，然后介绍开发过程中的具体技术，最后给出了泰州水利信息系统的一个实例。     

Stability of size-based scheduling disciplines in resource-sharing networks

Size-based scheduling strategies such as Shortest Remaining Processing Time first (SRPT) and Least Attained Service first (LAS) provide popular mechanisms for improving the overall delay performance by favoring smaller service requests over larger ones. The performance gains from these disciplines have been thoroughly investigated for single-server systems, and have also been experimentally demonstrated in web servers for example. In the present paper we explore the fundamental stability properties of size-based scheduling strategies in multi-resource systems, such as bandwidth-sharing networks, where users require service from several shared resources simultaneously. In particular, we establish the exact stability conditions for the SRPT and LAS disciplines in various limiting regimes. The results indicate that size-based scheduling strategies may fail to use the available resources efficiently, and in fact cause instability effects, even at arbitrarily low traffic loads, and will therefore not yield optimal delay performance. The qualitative findings confirm the tendency for users with long routes and large service requirements to experience severe performance degradation.     

Optimizing Grid-Based Workflow Execution

Large-scale applications can be expressed as a set of tasks with data dependencies between them, also known as application workflows. Due to the scale and data processing requirements of these applications, they require Grid computing and storage resources. So far, the focus has been on developing easy to use interfaces for composing these workflows and finding an optimal mapping of tasks in the workflow to the Grid resources in order to minimize the completion time of the application. After this mapping is done, a workflow execution engine is required to run the workflow over the mapped resources. In this paper, we show that the performance of the workflow execution engine in executing the workflow can also be a critical factor in determining the workflow completion time. Using Condor as the workflow execution engine, we examine the various factors that affect the completion time of a fine granularity astronomy workflow. We show that changing the system parameters that influence these factors and restructuring the workflow can drastically reduce the completion time of this class of workflows. We also examine the effect on the optimizations developed for the astronomy application on a coarser granularity biology application. We were able to reduce the completion time of the Montage and the Tomography application workflows by 90% and 50%, respectively.     

A Taxonomy of Workflow Management Systems for Grid Computing

With the advent of Grid and application technologies, scientists and engineers are building more and more complex applications to manage and process large data sets, and execute scientific experiments on distributed resources. Such application scenarios require means for composing and executing complex workflows. Therefore, many efforts have been made towards the development of workflow management systems for Grid computing. In this paper, we propose a taxonomy that characterizes and classifies various approaches for building and executing workflows on Grids. We also survey several representative Grid workflow systems developed by various projects world-wide to demonstrate the comprehensiveness of the taxonomy. The taxonomy not only highlights the design and engineering similarities and differences of state-of-the-art in Grid workflow systems, but also identifies the areas that need further research.     

电力无线专网中面向安全风险的分布式资源分配方法

针对电力无线专网中强干扰、高故障风险等场景下保障终端通信的问题，提出了一种面向安全风险的高能效分布式资源分配方法。首先，分析基站的能耗组成，建立系统能效最大化的资源分配模型；然后，采用K-means++算法对网络中的基站进行分簇，从而将整个网络划分成多个独立区域，并在各个簇内单独处理高风险基站；其次，在每个簇内，基于基站的风险值对高风险基站进行休眠，并把高风险基站下的用户转移连接到同一簇内的其他基站；最后，在各个簇内进一步优化正常工作基站的传输功率。理论分析和仿真实验结果表明，基站分簇操作大幅降低了基站休眠和功率优化分配的复杂度，并且在关闭了高风险基站之后，整体网络的能效从0.158 9 Mb/J提升至0.195 4 Mb/J。所提的分布式资源分配方法能够有效提高系统的能量效率。