映射的自然扩展与L-Fuzzy判断矩阵

通过映射的自然扩展,纠正了现行三角模糊数互反与互补判断矩阵的相互转换及一致性研究中的错误,推广了相关的概念及结果(包括排序向量的求法).     

一个局部带优先权的最大多物资网络流问题

给出一个局部带优先权的最大多物资网络流问题(MMFP-LPRI),证明它的解存在,并给出其η-松弛解的定义.通过做辅助网络,并运用程丛电等根据Korte和Vygen于2000年在Young,Garg和K(o|¨)nemann等工作的基础上给出的求最大多种物资网络流问题的ε-近似解的多项式方案设计的一个算法作为子程序进行二分收索建立了一个求所给问题的η-松弛解的拟多项式算法.最后,进行算法分析,证明了所设计的算法的输出结果确实是MMFP-LPRT的一个η-松弛解.     

基于小波包分解和FK分析的次声信号参数估计

频率波数分析法是一种估计信号慢度和方位角的台阵数据处理方法,在地震波信号处理中得到广泛应用,但将频率波数分析法应用于次声信号的时候,分辨率不高,易受噪声的影响,伪峰较明显。因此,本文提出了一种基于小波包分解和FK分析的次声信号参数估计方法,该方法借助小波包分解对信号整个频带的分辨能力,有效提高了算法的分辨率,降低了噪声的影响,有效压制了伪峰,并利用高斯调制正弦信号模拟次声信号,对比分析了方位角的均值、方差和均方根误差,验证了算法的性能,最后利用IS45台站接收的实际次声数据对算法进行对比分析,进一步验证了算法的有效性。     

Use of Commercial Acrylonitrile Standard for Wastewater Analysis

Abstract

It was found that a commercially available aqueous standard solution of acrylonitrile (1 mg/ml) was below manufacturer specification in concentration when compared to an authentic standard prepared from the pure compound. Comparative analyses of the two solutions, commercial and laboratory prepared acrylonitrile, were conducted by gas chromatography using a flame ionization detector with analytical conditions similar to those recommended by the EPA for acrylonitrile analyses. The acrylonitrile content of the commercial solution was found to be approximately 30% lower than specified. Commercial venders have provided solutions of the 114 organic priority pollutants which are convenient for instrumental calibration. There needs to be concern for experimental results reported with regards to accuracy and estimated detection limit when using such standards.     

面向单小批量产品设计的质量屋模型改进研究

为了使单小批量产品设计能够充分满足顾客需求,提高顾客满意度和忠诚度,帮助企业获得市场竞争优势。本文结合单小批量产品生产自身的特点,在系统的研究和总结传统的质量屋理论与方法及最新进展的基础上,对质量屋模型进行改进,利用设计规则间的影响系数和客户需求与设计规则之间的关系矩阵求出价值矩阵后,借助0—1整数规划技术求解改进的质量屋模型,从而使单小批量产品的设计规则可以按照顾客需求重新排列优先次序,最后通过S公司某单小批量产品的设计过程对模型进行验证。本文的研究意义在于使单小批量产品设计能够完全满足顾客的个性化需求,从而保证了企业最终生产出符合顾客和市场需求的单小批量产品。     

基于有穷损害优先法求解组合拍卖竞胜标问题研究

迄今为止,组合拍卖竞胜标问题并不存在一个多项式时间复杂度的算法,其计算复杂性与拍卖效率之间的矛盾一直是影响组合拍卖广泛应用的主要障碍。它是一个NP难问题,也是组合拍卖机制设计中的难题之一。而有穷损害优先方法是纯粹递归论中的一个十分重要的现代方法,特别对NP难问题求解算法的设计,对研究依复杂度决定的偏序结构的构造是一个很基本的有用工具。因此,本文提出根据组合拍卖的内在特性,将各不同的拍卖商品按照拍卖机制的要求,并结合其自身的协同价值等因素,设定一个优先序,然后采用有穷损害优先法有效有序地解决。     

M/M/1 Queue with Impatient Customers of Higher Priority

We introduce a simple approach for the analysis of the M/M/c queues with a single class of customers and constant impatience time by finding simple Markov processes (see (2.1) and (2.15) below), and then by applying this approach we analyze the M/M/1 queues with two classes of customers in which class 1 customers have impatience of constant duration, and class 2 customers have no impatience and lower priority than class 1 customers.     

Tail probabilities of low-priority waiting times and queue lengths in MAP/GI/1 queues

We consider the problem of estimating tail probabilities of waiting times in statistical multiplexing systems with two classes of sources – one with high priority and the other with low priority. The priority discipline is assumed to be nonpreemptive. Exact expressions for the transforms of these quantities are derived assuming that packet or cell streams are generated by Markovian Arrival Processes (MAPs). Then a numerical investigation of the large-buffer asymptotic behavior of the the waiting-time distribution for low-priority sources shows that these asymptotics are often non-exponential.     

Data Rate Aware Reliable Transmission Mechanism in Wireless Sensor Networks using Bayesian Regularized Neural Network approach

Wireless Sensor Networks consists of interconnected nodes that exchange information wirelessly enabling its deployment in innovative application areas. Network reliability streamline this exchange of information and communication technology to improve the overall performance of the network. The network reliability is categorized as: node reliability and link reliability. In this article, the node reliability is quantified with the help of packet reliability. The packet reliability is enhanced by optimizing the data rate using Bayesian Regularized Neural Network approach, which thus makes the network more reliable and sustainable. The optimization is carried out in three phases: network designing, data rate prediction and reliability evaluation. The network design includes the deployment of sensor nodes for gathering the communication data using NS-2.35. In the next phase, data rate prediction is carried out to enhance the reliability of the network. The reliability of a network is directly influenced by the packet loss ratio. According to research and the network experts, the acceptable threshold limit for the packet loss ratio is 5 percent. The data rate prediction is carried out to minimize the packet loss using the Bayesian Regularized Neural Network algorithm. The packet reliability is measured in terms of packet loss across the wireless network. Finally, a novel framework is presented for evaluating the packet reliability of the wireless network.